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Understanding Data Presentations (Guide + Examples)

In this age of overwhelming information, the skill to effectively convey data has become extremely valuable. Initiating a discussion on data presentation types involves thoughtful consideration of the nature of your data and the message you aim to convey. Different types of visualizations serve distinct purposes. Whether you’re dealing with how to develop a report or simply trying to communicate complex information, how you present data influences how well your audience understands and engages with it. This extensive guide leads you through the different ways of data presentation.

Table of Contents

What is a Data Presentation?

What should a data presentation include, line graphs, treemap chart, scatter plot, how to choose a data presentation type, recommended data presentation templates, common mistakes done in data presentation.

A data presentation is a slide deck that aims to disclose quantitative information to an audience through the use of visual formats and narrative techniques derived from data analysis, making complex data understandable and actionable. This process requires a series of tools, such as charts, graphs, tables, infographics, dashboards, and so on, supported by concise textual explanations to improve understanding and boost retention rate.

Data presentations require us to cull data in a format that allows the presenter to highlight trends, patterns, and insights so that the audience can act upon the shared information. In a few words, the goal of data presentations is to enable viewers to grasp complicated concepts or trends quickly, facilitating informed decision-making or deeper analysis.

Data presentations go beyond the mere usage of graphical elements. Seasoned presenters encompass visuals with the art of data storytelling , so the speech skillfully connects the points through a narrative that resonates with the audience. Depending on the purpose – inspire, persuade, inform, support decision-making processes, etc. – is the data presentation format that is better suited to help us in this journey.

To nail your upcoming data presentation, ensure to count with the following elements:

• Clear Objectives: Understand the intent of your presentation before selecting the graphical layout and metaphors to make content easier to grasp.
• Engaging introduction: Use a powerful hook from the get-go. For instance, you can ask a big question or present a problem that your data will answer. Take a look at our guide on how to start a presentation for tips & insights.
• Structured Narrative: Your data presentation must tell a coherent story. This means a beginning where you present the context, a middle section in which you present the data, and an ending that uses a call-to-action. Check our guide on presentation structure for further information.
• Visual Elements: These are the charts, graphs, and other elements of visual communication we ought to use to present data. This article will cover one by one the different types of data representation methods we can use, and provide further guidance on choosing between them.
• Insights and Analysis: This is not just showcasing a graph and letting people get an idea about it. A proper data presentation includes the interpretation of that data, the reason why it’s included, and why it matters to your research.
• Conclusion & CTA: Ending your presentation with a call to action is necessary. Whether you intend to wow your audience into acquiring your services, inspire them to change the world, or whatever the purpose of your presentation, there must be a stage in which you convey all that you shared and show the path to staying in touch. Plan ahead whether you want to use a thank-you slide, a video presentation, or which method is apt and tailored to the kind of presentation you deliver.
• Q&A Session: After your speech is concluded, allocate 3-5 minutes for the audience to raise any questions about the information you disclosed. This is an extra chance to establish your authority on the topic. Check our guide on questions and answer sessions in presentations here.

Bar charts are a graphical representation of data using rectangular bars to show quantities or frequencies in an established category. They make it easy for readers to spot patterns or trends. Bar charts can be horizontal or vertical, although the vertical format is commonly known as a column chart. They display categorical, discrete, or continuous variables grouped in class intervals [1] . They include an axis and a set of labeled bars horizontally or vertically. These bars represent the frequencies of variable values or the values themselves. Numbers on the y-axis of a vertical bar chart or the x-axis of a horizontal bar chart are called the scale.

Real-Life Application of Bar Charts

Let’s say a sales manager is presenting sales to their audience. Using a bar chart, he follows these steps.

Step 1: Selecting Data

The first step is to identify the specific data you will present to your audience.

The sales manager has highlighted these products for the presentation.

• Product A: Men’s Shoes
• Product B: Women’s Apparel
• Product C: Electronics
• Product D: Home Decor

Step 2: Choosing Orientation

Opt for a vertical layout for simplicity. Vertical bar charts help compare different categories in case there are not too many categories [1] . They can also help show different trends. A vertical bar chart is used where each bar represents one of the four chosen products. After plotting the data, it is seen that the height of each bar directly represents the sales performance of the respective product.

It is visible that the tallest bar (Electronics – Product C) is showing the highest sales. However, the shorter bars (Women’s Apparel – Product B and Home Decor – Product D) need attention. It indicates areas that require further analysis or strategies for improvement.

Step 3: Colorful Insights

Different colors are used to differentiate each product. It is essential to show a color-coded chart where the audience can distinguish between products.

• Men’s Shoes (Product A): Yellow
• Women’s Apparel (Product B): Orange
• Electronics (Product C): Violet
• Home Decor (Product D): Blue

Bar charts are straightforward and easily understandable for presenting data. They are versatile when comparing products or any categorical data [2] . Bar charts adapt seamlessly to retail scenarios. Despite that, bar charts have a few shortcomings. They cannot illustrate data trends over time. Besides, overloading the chart with numerous products can lead to visual clutter, diminishing its effectiveness.

For more information, check our collection of bar chart templates for PowerPoint .

Line graphs help illustrate data trends, progressions, or fluctuations by connecting a series of data points called ‘markers’ with straight line segments. This provides a straightforward representation of how values change [5] . Their versatility makes them invaluable for scenarios requiring a visual understanding of continuous data. In addition, line graphs are also useful for comparing multiple datasets over the same timeline. Using multiple line graphs allows us to compare more than one data set. They simplify complex information so the audience can quickly grasp the ups and downs of values. From tracking stock prices to analyzing experimental results, you can use line graphs to show how data changes over a continuous timeline. They show trends with simplicity and clarity.

Real-life Application of Line Graphs

To understand line graphs thoroughly, we will use a real case. Imagine you’re a financial analyst presenting a tech company’s monthly sales for a licensed product over the past year. Investors want insights into sales behavior by month, how market trends may have influenced sales performance and reception to the new pricing strategy. To present data via a line graph, you will complete these steps.

First, you need to gather the data. In this case, your data will be the sales numbers. For example:

• January: $45,000
• February: $55,000
• March: $45,000
• April: $60,000
• May: $ 70,000
• June: $65,000
• July: $62,000
• August: $68,000
• September: $81,000
• October: $76,000
• November: $87,000
• December: $91,000

After choosing the data, the next step is to select the orientation. Like bar charts, you can use vertical or horizontal line graphs. However, we want to keep this simple, so we will keep the timeline (x-axis) horizontal while the sales numbers (y-axis) vertical.

Step 3: Connecting Trends

After adding the data to your preferred software, you will plot a line graph. In the graph, each month’s sales are represented by data points connected by a line.

Step 4: Adding Clarity with Color

If there are multiple lines, you can also add colors to highlight each one, making it easier to follow.

Line graphs excel at visually presenting trends over time. These presentation aids identify patterns, like upward or downward trends. However, too many data points can clutter the graph, making it harder to interpret. Line graphs work best with continuous data but are not suitable for categories.

For more information, check our collection of line chart templates for PowerPoint and our article about how to make a presentation graph .

A data dashboard is a visual tool for analyzing information. Different graphs, charts, and tables are consolidated in a layout to showcase the information required to achieve one or more objectives. Dashboards help quickly see Key Performance Indicators (KPIs). You don’t make new visuals in the dashboard; instead, you use it to display visuals you’ve already made in worksheets [3] .

Keeping the number of visuals on a dashboard to three or four is recommended. Adding too many can make it hard to see the main points [4]. Dashboards can be used for business analytics to analyze sales, revenue, and marketing metrics at a time. They are also used in the manufacturing industry, as they allow users to grasp the entire production scenario at the moment while tracking the core KPIs for each line.

Real-Life Application of a Dashboard

Consider a project manager presenting a software development project’s progress to a tech company’s leadership team. He follows the following steps.

Step 1: Defining Key Metrics

To effectively communicate the project’s status, identify key metrics such as completion status, budget, and bug resolution rates. Then, choose measurable metrics aligned with project objectives.

Step 2: Choosing Visualization Widgets

After finalizing the data, presentation aids that align with each metric are selected. For this project, the project manager chooses a progress bar for the completion status and uses bar charts for budget allocation. Likewise, he implements line charts for bug resolution rates.

Step 3: Dashboard Layout

Key metrics are prominently placed in the dashboard for easy visibility, and the manager ensures that it appears clean and organized.

Dashboards provide a comprehensive view of key project metrics. Users can interact with data, customize views, and drill down for detailed analysis. However, creating an effective dashboard requires careful planning to avoid clutter. Besides, dashboards rely on the availability and accuracy of underlying data sources.

For more information, check our article on how to design a dashboard presentation , and discover our collection of dashboard PowerPoint templates .

Treemap charts represent hierarchical data structured in a series of nested rectangles [6] . As each branch of the ‘tree’ is given a rectangle, smaller tiles can be seen representing sub-branches, meaning elements on a lower hierarchical level than the parent rectangle. Each one of those rectangular nodes is built by representing an area proportional to the specified data dimension.

Treemaps are useful for visualizing large datasets in compact space. It is easy to identify patterns, such as which categories are dominant. Common applications of the treemap chart are seen in the IT industry, such as resource allocation, disk space management, website analytics, etc. Also, they can be used in multiple industries like healthcare data analysis, market share across different product categories, or even in finance to visualize portfolios.

Real-Life Application of a Treemap Chart

Let’s consider a financial scenario where a financial team wants to represent the budget allocation of a company. There is a hierarchy in the process, so it is helpful to use a treemap chart. In the chart, the top-level rectangle could represent the total budget, and it would be subdivided into smaller rectangles, each denoting a specific department. Further subdivisions within these smaller rectangles might represent individual projects or cost categories.

Step 1: Define Your Data Hierarchy

While presenting data on the budget allocation, start by outlining the hierarchical structure. The sequence will be like the overall budget at the top, followed by departments, projects within each department, and finally, individual cost categories for each project.

• Top-level rectangle: Total Budget
• Second-level rectangles: Departments (Engineering, Marketing, Sales)
• Third-level rectangles: Projects within each department
• Fourth-level rectangles: Cost categories for each project (Personnel, Marketing Expenses, Equipment)

Step 2: Choose a Suitable Tool

It’s time to select a data visualization tool supporting Treemaps. Popular choices include Tableau, Microsoft Power BI, PowerPoint, or even coding with libraries like D3.js. It is vital to ensure that the chosen tool provides customization options for colors, labels, and hierarchical structures.

Here, the team uses PowerPoint for this guide because of its user-friendly interface and robust Treemap capabilities.

Step 3: Make a Treemap Chart with PowerPoint

After opening the PowerPoint presentation, they chose “SmartArt” to form the chart. The SmartArt Graphic window has a “Hierarchy” category on the left.  Here, you will see multiple options. You can choose any layout that resembles a Treemap. The “Table Hierarchy” or “Organization Chart” options can be adapted. The team selects the Table Hierarchy as it looks close to a Treemap.

Step 5: Input Your Data

After that, a new window will open with a basic structure. They add the data one by one by clicking on the text boxes. They start with the top-level rectangle, representing the total budget.  

Step 6: Customize the Treemap

By clicking on each shape, they customize its color, size, and label. At the same time, they can adjust the font size, style, and color of labels by using the options in the “Format” tab in PowerPoint. Using different colors for each level enhances the visual difference.

Treemaps excel at illustrating hierarchical structures. These charts make it easy to understand relationships and dependencies. They efficiently use space, compactly displaying a large amount of data, reducing the need for excessive scrolling or navigation. Additionally, using colors enhances the understanding of data by representing different variables or categories.

In some cases, treemaps might become complex, especially with deep hierarchies.  It becomes challenging for some users to interpret the chart. At the same time, displaying detailed information within each rectangle might be constrained by space. It potentially limits the amount of data that can be shown clearly. Without proper labeling and color coding, there’s a risk of misinterpretation.

A heatmap is a data visualization tool that uses color coding to represent values across a two-dimensional surface. In these, colors replace numbers to indicate the magnitude of each cell. This color-shaded matrix display is valuable for summarizing and understanding data sets with a glance [7] . The intensity of the color corresponds to the value it represents, making it easy to identify patterns, trends, and variations in the data.

As a tool, heatmaps help businesses analyze website interactions, revealing user behavior patterns and preferences to enhance overall user experience. In addition, companies use heatmaps to assess content engagement, identifying popular sections and areas of improvement for more effective communication. They excel at highlighting patterns and trends in large datasets, making it easy to identify areas of interest.

We can implement heatmaps to express multiple data types, such as numerical values, percentages, or even categorical data. Heatmaps help us easily spot areas with lots of activity, making them helpful in figuring out clusters [8] . When making these maps, it is important to pick colors carefully. The colors need to show the differences between groups or levels of something. And it is good to use colors that people with colorblindness can easily see.

Check our detailed guide on how to create a heatmap here. Also discover our collection of heatmap PowerPoint templates .

Pie charts are circular statistical graphics divided into slices to illustrate numerical proportions. Each slice represents a proportionate part of the whole, making it easy to visualize the contribution of each component to the total.

The size of the pie charts is influenced by the value of data points within each pie. The total of all data points in a pie determines its size. The pie with the highest data points appears as the largest, whereas the others are proportionally smaller. However, you can present all pies of the same size if proportional representation is not required [9] . Sometimes, pie charts are difficult to read, or additional information is required. A variation of this tool can be used instead, known as the donut chart , which has the same structure but a blank center, creating a ring shape. Presenters can add extra information, and the ring shape helps to declutter the graph.

Pie charts are used in business to show percentage distribution, compare relative sizes of categories, or present straightforward data sets where visualizing ratios is essential.

Real-Life Application of Pie Charts

Consider a scenario where you want to represent the distribution of the data. Each slice of the pie chart would represent a different category, and the size of each slice would indicate the percentage of the total portion allocated to that category.

Step 1: Define Your Data Structure

Imagine you are presenting the distribution of a project budget among different expense categories.

• Column A: Expense Categories (Personnel, Equipment, Marketing, Miscellaneous)
• Column B: Budget Amounts ($40,000, $30,000, $20,000, $10,000) Column B represents the values of your categories in Column A.

Step 2: Insert a Pie Chart

Using any of the accessible tools, you can create a pie chart. The most convenient tools for forming a pie chart in a presentation are presentation tools such as PowerPoint or Google Slides.  You will notice that the pie chart assigns each expense category a percentage of the total budget by dividing it by the total budget.

For instance:

• Personnel: $40,000 / ($40,000 + $30,000 + $20,000 + $10,000) = 40%
• Equipment: $30,000 / ($40,000 + $30,000 + $20,000 + $10,000) = 30%
• Marketing: $20,000 / ($40,000 + $30,000 + $20,000 + $10,000) = 20%
• Miscellaneous: $10,000 / ($40,000 + $30,000 + $20,000 + $10,000) = 10%

You can make a chart out of this or just pull out the pie chart from the data.

3D pie charts and 3D donut charts are quite popular among the audience. They stand out as visual elements in any presentation slide, so let’s take a look at how our pie chart example would look in 3D pie chart format.

Step 03: Results Interpretation

The pie chart visually illustrates the distribution of the project budget among different expense categories. Personnel constitutes the largest portion at 40%, followed by equipment at 30%, marketing at 20%, and miscellaneous at 10%. This breakdown provides a clear overview of where the project funds are allocated, which helps in informed decision-making and resource management. It is evident that personnel are a significant investment, emphasizing their importance in the overall project budget.

Pie charts provide a straightforward way to represent proportions and percentages. They are easy to understand, even for individuals with limited data analysis experience. These charts work well for small datasets with a limited number of categories.

However, a pie chart can become cluttered and less effective in situations with many categories. Accurate interpretation may be challenging, especially when dealing with slight differences in slice sizes. In addition, these charts are static and do not effectively convey trends over time.

For more information, check our collection of pie chart templates for PowerPoint .

Histograms present the distribution of numerical variables. Unlike a bar chart that records each unique response separately, histograms organize numeric responses into bins and show the frequency of reactions within each bin [10] . The x-axis of a histogram shows the range of values for a numeric variable. At the same time, the y-axis indicates the relative frequencies (percentage of the total counts) for that range of values.

Whenever you want to understand the distribution of your data, check which values are more common, or identify outliers, histograms are your go-to. Think of them as a spotlight on the story your data is telling. A histogram can provide a quick and insightful overview if you’re curious about exam scores, sales figures, or any numerical data distribution.

Real-Life Application of a Histogram

In the histogram data analysis presentation example, imagine an instructor analyzing a class’s grades to identify the most common score range. A histogram could effectively display the distribution. It will show whether most students scored in the average range or if there are significant outliers.

Step 1: Gather Data

He begins by gathering the data. The scores of each student in class are gathered to analyze exam scores.

After arranging the scores in ascending order, bin ranges are set.

Step 2: Define Bins

Bins are like categories that group similar values. Think of them as buckets that organize your data. The presenter decides how wide each bin should be based on the range of the values. For instance, the instructor sets the bin ranges based on score intervals: 60-69, 70-79, 80-89, and 90-100.

Step 3: Count Frequency

Now, he counts how many data points fall into each bin. This step is crucial because it tells you how often specific ranges of values occur. The result is the frequency distribution, showing the occurrences of each group.

Here, the instructor counts the number of students in each category.

• 60-69: 1 student (Kate)
• 70-79: 4 students (David, Emma, Grace, Jack)
• 80-89: 7 students (Alice, Bob, Frank, Isabel, Liam, Mia, Noah)
• 90-100: 3 students (Clara, Henry, Olivia)

Step 4: Create the Histogram

It’s time to turn the data into a visual representation. Draw a bar for each bin on a graph. The width of the bar should correspond to the range of the bin, and the height should correspond to the frequency.  To make your histogram understandable, label the X and Y axes.

In this case, the X-axis should represent the bins (e.g., test score ranges), and the Y-axis represents the frequency.

The histogram of the class grades reveals insightful patterns in the distribution. Most students, with seven students, fall within the 80-89 score range. The histogram provides a clear visualization of the class’s performance. It showcases a concentration of grades in the upper-middle range with few outliers at both ends. This analysis helps in understanding the overall academic standing of the class. It also identifies the areas for potential improvement or recognition.

Thus, histograms provide a clear visual representation of data distribution. They are easy to interpret, even for those without a statistical background. They apply to various types of data, including continuous and discrete variables. One weak point is that histograms do not capture detailed patterns in students’ data, with seven compared to other visualization methods.

A scatter plot is a graphical representation of the relationship between two variables. It consists of individual data points on a two-dimensional plane. This plane plots one variable on the x-axis and the other on the y-axis. Each point represents a unique observation. It visualizes patterns, trends, or correlations between the two variables.

Scatter plots are also effective in revealing the strength and direction of relationships. They identify outliers and assess the overall distribution of data points. The points’ dispersion and clustering reflect the relationship’s nature, whether it is positive, negative, or lacks a discernible pattern. In business, scatter plots assess relationships between variables such as marketing cost and sales revenue. They help present data correlations and decision-making.

Real-Life Application of Scatter Plot

A group of scientists is conducting a study on the relationship between daily hours of screen time and sleep quality. After reviewing the data, they managed to create this table to help them build a scatter plot graph:

In the provided example, the x-axis represents Daily Hours of Screen Time, and the y-axis represents the Sleep Quality Rating.

The scientists observe a negative correlation between the amount of screen time and the quality of sleep. This is consistent with their hypothesis that blue light, especially before bedtime, has a significant impact on sleep quality and metabolic processes.

There are a few things to remember when using a scatter plot. Even when a scatter diagram indicates a relationship, it doesn’t mean one variable affects the other. A third factor can influence both variables. The more the plot resembles a straight line, the stronger the relationship is perceived [11] . If it suggests no ties, the observed pattern might be due to random fluctuations in data. When the scatter diagram depicts no correlation, whether the data might be stratified is worth considering.

Choosing the appropriate data presentation type is crucial when making a presentation . Understanding the nature of your data and the message you intend to convey will guide this selection process. For instance, when showcasing quantitative relationships, scatter plots become instrumental in revealing correlations between variables. If the focus is on emphasizing parts of a whole, pie charts offer a concise display of proportions. Histograms, on the other hand, prove valuable for illustrating distributions and frequency patterns. 

Bar charts provide a clear visual comparison of different categories. Likewise, line charts excel in showcasing trends over time, while tables are ideal for detailed data examination. Starting a presentation on data presentation types involves evaluating the specific information you want to communicate and selecting the format that aligns with your message. This ensures clarity and resonance with your audience from the beginning of your presentation.

1. Fact Sheet Dashboard for Data Presentation

Convey all the data you need to present in this one-pager format, an ideal solution tailored for users looking for presentation aids. Global maps, donut chats, column graphs, and text neatly arranged in a clean layout presented in light and dark themes.

Use This Template

2. 3D Column Chart Infographic PPT Template

Represent column charts in a highly visual 3D format with this PPT template. A creative way to present data, this template is entirely editable, and we can craft either a one-page infographic or a series of slides explaining what we intend to disclose point by point.

3. Data Circles Infographic PowerPoint Template

An alternative to the pie chart and donut chart diagrams, this template features a series of curved shapes with bubble callouts as ways of presenting data. Expand the information for each arch in the text placeholder areas.

4. Colorful Metrics Dashboard for Data Presentation

This versatile dashboard template helps us in the presentation of the data by offering several graphs and methods to convert numbers into graphics. Implement it for e-commerce projects, financial projections, project development, and more.

5. Animated Data Presentation Tools for PowerPoint & Google Slides

A slide deck filled with most of the tools mentioned in this article, from bar charts, column charts, treemap graphs, pie charts, histogram, etc. Animated effects make each slide look dynamic when sharing data with stakeholders.

6. Statistics Waffle Charts PPT Template for Data Presentations

This PPT template helps us how to present data beyond the typical pie chart representation. It is widely used for demographics, so it’s a great fit for marketing teams, data science professionals, HR personnel, and more.

7. Data Presentation Dashboard Template for Google Slides

A compendium of tools in dashboard format featuring line graphs, bar charts, column charts, and neatly arranged placeholder text areas. 

8. Weather Dashboard for Data Presentation

Share weather data for agricultural presentation topics, environmental studies, or any kind of presentation that requires a highly visual layout for weather forecasting on a single day. Two color themes are available.

9. Social Media Marketing Dashboard Data Presentation Template

Intended for marketing professionals, this dashboard template for data presentation is a tool for presenting data analytics from social media channels. Two slide layouts featuring line graphs and column charts.

10. Project Management Summary Dashboard Template

A tool crafted for project managers to deliver highly visual reports on a project’s completion, the profits it delivered for the company, and expenses/time required to execute it. 4 different color layouts are available.

11. Profit & Loss Dashboard for PowerPoint and Google Slides

A must-have for finance professionals. This typical profit & loss dashboard includes progress bars, donut charts, column charts, line graphs, and everything that’s required to deliver a comprehensive report about a company’s financial situation.

Overwhelming visuals

One of the mistakes related to using data-presenting methods is including too much data or using overly complex visualizations. They can confuse the audience and dilute the key message.

Inappropriate chart types

Choosing the wrong type of chart for the data at hand can lead to misinterpretation. For example, using a pie chart for data that doesn’t represent parts of a whole is not right.

Lack of context

Failing to provide context or sufficient labeling can make it challenging for the audience to understand the significance of the presented data.

Inconsistency in design

Using inconsistent design elements and color schemes across different visualizations can create confusion and visual disarray.

Failure to provide details

Simply presenting raw data without offering clear insights or takeaways can leave the audience without a meaningful conclusion.

Lack of focus

Not having a clear focus on the key message or main takeaway can result in a presentation that lacks a central theme.

Visual accessibility issues

Overlooking the visual accessibility of charts and graphs can exclude certain audience members who may have difficulty interpreting visual information.

In order to avoid these mistakes in data presentation, presenters can benefit from using presentation templates . These templates provide a structured framework. They ensure consistency, clarity, and an aesthetically pleasing design, enhancing data communication’s overall impact.

Understanding and choosing data presentation types are pivotal in effective communication. Each method serves a unique purpose, so selecting the appropriate one depends on the nature of the data and the message to be conveyed. The diverse array of presentation types offers versatility in visually representing information, from bar charts showing values to pie charts illustrating proportions. 

Using the proper method enhances clarity, engages the audience, and ensures that data sets are not just presented but comprehensively understood. By appreciating the strengths and limitations of different presentation types, communicators can tailor their approach to convey information accurately, developing a deeper connection between data and audience understanding.

[1] Government of Canada, S.C. (2021) 5 Data Visualization 5.2 Bar Chart , 5.2 Bar chart .  https://www150.statcan.gc.ca/n1/edu/power-pouvoir/ch9/bargraph-diagrammeabarres/5214818-eng.htm

[2] Kosslyn, S.M., 1989. Understanding charts and graphs. Applied cognitive psychology, 3(3), pp.185-225. https://apps.dtic.mil/sti/pdfs/ADA183409.pdf

[3] Creating a Dashboard . https://it.tufts.edu/book/export/html/1870

[4] https://www.goldenwestcollege.edu/research/data-and-more/data-dashboards/index.html

[5] https://www.mit.edu/course/21/21.guide/grf-line.htm

[6] Jadeja, M. and Shah, K., 2015, January. Tree-Map: A Visualization Tool for Large Data. In GSB@ SIGIR (pp. 9-13). https://ceur-ws.org/Vol-1393/gsb15proceedings.pdf#page=15

[7] Heat Maps and Quilt Plots. https://www.publichealth.columbia.edu/research/population-health-methods/heat-maps-and-quilt-plots

[8] EIU QGIS WORKSHOP. https://www.eiu.edu/qgisworkshop/heatmaps.php

[9] About Pie Charts.  https://www.mit.edu/~mbarker/formula1/f1help/11-ch-c8.htm

[10] Histograms. https://sites.utexas.edu/sos/guided/descriptive/numericaldd/descriptiven2/histogram/ [11] https://asq.org/quality-resources/scatter-diagram

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Graphical Representation of Data

Graphical representation of data is an attractive method of showcasing numerical data that help in analyzing and representing quantitative data visually. A graph is a kind of a chart where data are plotted as variables across the coordinate. It became easy to analyze the extent of change of one variable based on the change of other variables. Graphical representation of data is done through different mediums such as lines, plots, diagrams, etc. Let us learn more about this interesting concept of graphical representation of data, the different types, and solve a few examples.

Definition of Graphical Representation of Data

A graphical representation is a visual representation of data statistics-based results using graphs, plots, and charts. This kind of representation is more effective in understanding and comparing data than seen in a tabular form. Graphical representation helps to qualify, sort, and present data in a method that is simple to understand for a larger audience. Graphs enable in studying the cause and effect relationship between two variables through both time series and frequency distribution. The data that is obtained from different surveying is infused into a graphical representation by the use of some symbols, such as lines on a line graph, bars on a bar chart, or slices of a pie chart. This visual representation helps in clarity, comparison, and understanding of numerical data.

Representation of Data

The word data is from the Latin word Datum, which means something given. The numerical figures collected through a survey are called data and can be represented in two forms - tabular form and visual form through graphs. Once the data is collected through constant observations, it is arranged, summarized, and classified to finally represented in the form of a graph. There are two kinds of data - quantitative and qualitative. Quantitative data is more structured, continuous, and discrete with statistical data whereas qualitative is unstructured where the data cannot be analyzed.

Principles of Graphical Representation of Data

The principles of graphical representation are algebraic. In a graph, there are two lines known as Axis or Coordinate axis. These are the X-axis and Y-axis. The horizontal axis is the X-axis and the vertical axis is the Y-axis. They are perpendicular to each other and intersect at O or point of Origin. On the right side of the Origin, the Xaxis has a positive value and on the left side, it has a negative value. In the same way, the upper side of the Origin Y-axis has a positive value where the down one is with a negative value. When -axis and y-axis intersect each other at the origin it divides the plane into four parts which are called Quadrant I, Quadrant II, Quadrant III, Quadrant IV. This form of representation is seen in a frequency distribution that is represented in four methods, namely Histogram, Smoothed frequency graph, Pie diagram or Pie chart, Cumulative or ogive frequency graph, and Frequency Polygon.

Advantages and Disadvantages of Graphical Representation of Data

Listed below are some advantages and disadvantages of using a graphical representation of data:

• It improves the way of analyzing and learning as the graphical representation makes the data easy to understand.
• It can be used in almost all fields from mathematics to physics to psychology and so on.
• It is easy to understand for its visual impacts.
• It shows the whole and huge data in an instance.
• It is mainly used in statistics to determine the mean, median, and mode for different data

The main disadvantage of graphical representation of data is that it takes a lot of effort as well as resources to find the most appropriate data and then represent it graphically.

Rules of Graphical Representation of Data

While presenting data graphically, there are certain rules that need to be followed. They are listed below:

• Suitable Title: The title of the graph should be appropriate that indicate the subject of the presentation.
• Measurement Unit: The measurement unit in the graph should be mentioned.
• Proper Scale: A proper scale needs to be chosen to represent the data accurately.
• Index: For better understanding, index the appropriate colors, shades, lines, designs in the graphs.
• Data Sources: Data should be included wherever it is necessary at the bottom of the graph.
• Simple: The construction of a graph should be easily understood.
• Neat: The graph should be visually neat in terms of size and font to read the data accurately.

Uses of Graphical Representation of Data

The main use of a graphical representation of data is understanding and identifying the trends and patterns of the data. It helps in analyzing large quantities, comparing two or more data, making predictions, and building a firm decision. The visual display of data also helps in avoiding confusion and overlapping of any information. Graphs like line graphs and bar graphs, display two or more data clearly for easy comparison. This is important in communicating our findings to others and our understanding and analysis of the data.

Types of Graphical Representation of Data

Data is represented in different types of graphs such as plots, pies, diagrams, etc. They are as follows,

Related Topics

Listed below are a few interesting topics that are related to the graphical representation of data, take a look.

• x and y graph
• Frequency Polygon
• Cumulative Frequency

Examples on Graphical Representation of Data

Example 1 : A pie chart is divided into 3 parts with the angles measuring as 2x, 8x, and 10x respectively. Find the value of x in degrees.

We know, the sum of all angles in a pie chart would give 360º as result. ⇒ 2x + 8x + 10x = 360º ⇒ 20 x = 360º ⇒ x = 360º/20 ⇒ x = 18º Therefore, the value of x is 18º.

Example 2: Ben is trying to read the plot given below. His teacher has given him stem and leaf plot worksheets. Can you help him answer the questions? i) What is the mode of the plot? ii) What is the mean of the plot? iii) Find the range.

Solution: i) Mode is the number that appears often in the data. Leaf 4 occurs twice on the plot against stem 5.

Hence, mode = 54

ii) The sum of all data values is 12 + 14 + 21 + 25 + 28 + 32 + 34 + 36 + 50 + 53 + 54 + 54 + 62 + 65 + 67 + 83 + 88 + 89 + 91 = 958

To find the mean, we have to divide the sum by the total number of values.

Mean = Sum of all data values ÷ 19 = 958 ÷ 19 = 50.42

iii) Range = the highest value - the lowest value = 91 - 12 = 79

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Practice Questions on Graphical Representation of Data

Faqs on graphical representation of data, what is graphical representation.

Graphical representation is a form of visually displaying data through various methods like graphs, diagrams, charts, and plots. It helps in sorting, visualizing, and presenting data in a clear manner through different types of graphs. Statistics mainly use graphical representation to show data.

What are the Different Types of Graphical Representation?

The different types of graphical representation of data are:

• Stem and leaf plot
• Scatter diagrams
• Frequency Distribution

Is the Graphical Representation of Numerical Data?

Yes, these graphical representations are numerical data that has been accumulated through various surveys and observations. The method of presenting these numerical data is called a chart. There are different kinds of charts such as a pie chart, bar graph, line graph, etc, that help in clearly showcasing the data.

What is the Use of Graphical Representation of Data?

Graphical representation of data is useful in clarifying, interpreting, and analyzing data plotting points and drawing line segments , surfaces, and other geometric forms or symbols.

What are the Ways to Represent Data?

Tables, charts, and graphs are all ways of representing data, and they can be used for two broad purposes. The first is to support the collection, organization, and analysis of data as part of the process of a scientific study.

What is the Objective of Graphical Representation of Data?

The main objective of representing data graphically is to display information visually that helps in understanding the information efficiently, clearly, and accurately. This is important to communicate the findings as well as analyze the data.

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17 Data Visualization Techniques All Professionals Should Know

• 17 Sep 2019

There’s a growing demand for business analytics and data expertise in the workforce. But you don’t need to be a professional analyst to benefit from data-related skills.

Becoming skilled at common data visualization techniques can help you reap the rewards of data-driven decision-making , including increased confidence and potential cost savings. Learning how to effectively visualize data could be the first step toward using data analytics and data science to your advantage to add value to your organization.

Several data visualization techniques can help you become more effective in your role. Here are 17 essential data visualization techniques all professionals should know, as well as tips to help you effectively present your data.

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What Is Data Visualization?

Data visualization is the process of creating graphical representations of information. This process helps the presenter communicate data in a way that’s easy for the viewer to interpret and draw conclusions.

There are many different techniques and tools you can leverage to visualize data, so you want to know which ones to use and when. Here are some of the most important data visualization techniques all professionals should know.

Data Visualization Techniques

The type of data visualization technique you leverage will vary based on the type of data you’re working with, in addition to the story you’re telling with your data .

Here are some important data visualization techniques to know:

• Gantt Chart
• Box and Whisker Plot
• Waterfall Chart
• Scatter Plot
• Pictogram Chart
• Highlight Table
• Bullet Graph
• Choropleth Map
• Network Diagram
• Correlation Matrices

1. Pie Chart

Pie charts are one of the most common and basic data visualization techniques, used across a wide range of applications. Pie charts are ideal for illustrating proportions, or part-to-whole comparisons.

Because pie charts are relatively simple and easy to read, they’re best suited for audiences who might be unfamiliar with the information or are only interested in the key takeaways. For viewers who require a more thorough explanation of the data, pie charts fall short in their ability to display complex information.

2. Bar Chart

The classic bar chart , or bar graph, is another common and easy-to-use method of data visualization. In this type of visualization, one axis of the chart shows the categories being compared, and the other, a measured value. The length of the bar indicates how each group measures according to the value.

One drawback is that labeling and clarity can become problematic when there are too many categories included. Like pie charts, they can also be too simple for more complex data sets.

3. Histogram

Unlike bar charts, histograms illustrate the distribution of data over a continuous interval or defined period. These visualizations are helpful in identifying where values are concentrated, as well as where there are gaps or unusual values.

Histograms are especially useful for showing the frequency of a particular occurrence. For instance, if you’d like to show how many clicks your website received each day over the last week, you can use a histogram. From this visualization, you can quickly determine which days your website saw the greatest and fewest number of clicks.

4. Gantt Chart

Gantt charts are particularly common in project management, as they’re useful in illustrating a project timeline or progression of tasks. In this type of chart, tasks to be performed are listed on the vertical axis and time intervals on the horizontal axis. Horizontal bars in the body of the chart represent the duration of each activity.

Utilizing Gantt charts to display timelines can be incredibly helpful, and enable team members to keep track of every aspect of a project. Even if you’re not a project management professional, familiarizing yourself with Gantt charts can help you stay organized.

5. Heat Map

A heat map is a type of visualization used to show differences in data through variations in color. These charts use color to communicate values in a way that makes it easy for the viewer to quickly identify trends. Having a clear legend is necessary in order for a user to successfully read and interpret a heatmap.

There are many possible applications of heat maps. For example, if you want to analyze which time of day a retail store makes the most sales, you can use a heat map that shows the day of the week on the vertical axis and time of day on the horizontal axis. Then, by shading in the matrix with colors that correspond to the number of sales at each time of day, you can identify trends in the data that allow you to determine the exact times your store experiences the most sales.

6. A Box and Whisker Plot

A box and whisker plot , or box plot, provides a visual summary of data through its quartiles. First, a box is drawn from the first quartile to the third of the data set. A line within the box represents the median. “Whiskers,” or lines, are then drawn extending from the box to the minimum (lower extreme) and maximum (upper extreme). Outliers are represented by individual points that are in-line with the whiskers.

This type of chart is helpful in quickly identifying whether or not the data is symmetrical or skewed, as well as providing a visual summary of the data set that can be easily interpreted.

7. Waterfall Chart

A waterfall chart is a visual representation that illustrates how a value changes as it’s influenced by different factors, such as time. The main goal of this chart is to show the viewer how a value has grown or declined over a defined period. For example, waterfall charts are popular for showing spending or earnings over time.

8. Area Chart

An area chart , or area graph, is a variation on a basic line graph in which the area underneath the line is shaded to represent the total value of each data point. When several data series must be compared on the same graph, stacked area charts are used.

This method of data visualization is useful for showing changes in one or more quantities over time, as well as showing how each quantity combines to make up the whole. Stacked area charts are effective in showing part-to-whole comparisons.

9. Scatter Plot

Another technique commonly used to display data is a scatter plot . A scatter plot displays data for two variables as represented by points plotted against the horizontal and vertical axis. This type of data visualization is useful in illustrating the relationships that exist between variables and can be used to identify trends or correlations in data.

Scatter plots are most effective for fairly large data sets, since it’s often easier to identify trends when there are more data points present. Additionally, the closer the data points are grouped together, the stronger the correlation or trend tends to be.

10. Pictogram Chart

Pictogram charts , or pictograph charts, are particularly useful for presenting simple data in a more visual and engaging way. These charts use icons to visualize data, with each icon representing a different value or category. For example, data about time might be represented by icons of clocks or watches. Each icon can correspond to either a single unit or a set number of units (for example, each icon represents 100 units).

In addition to making the data more engaging, pictogram charts are helpful in situations where language or cultural differences might be a barrier to the audience’s understanding of the data.

11. Timeline

Timelines are the most effective way to visualize a sequence of events in chronological order. They’re typically linear, with key events outlined along the axis. Timelines are used to communicate time-related information and display historical data.

Timelines allow you to highlight the most important events that occurred, or need to occur in the future, and make it easy for the viewer to identify any patterns appearing within the selected time period. While timelines are often relatively simple linear visualizations, they can be made more visually appealing by adding images, colors, fonts, and decorative shapes.

12. Highlight Table

A highlight table is a more engaging alternative to traditional tables. By highlighting cells in the table with color, you can make it easier for viewers to quickly spot trends and patterns in the data. These visualizations are useful for comparing categorical data.

Depending on the data visualization tool you’re using, you may be able to add conditional formatting rules to the table that automatically color cells that meet specified conditions. For instance, when using a highlight table to visualize a company’s sales data, you may color cells red if the sales data is below the goal, or green if sales were above the goal. Unlike a heat map, the colors in a highlight table are discrete and represent a single meaning or value.

13. Bullet Graph

A bullet graph is a variation of a bar graph that can act as an alternative to dashboard gauges to represent performance data. The main use for a bullet graph is to inform the viewer of how a business is performing in comparison to benchmarks that are in place for key business metrics.

In a bullet graph, the darker horizontal bar in the middle of the chart represents the actual value, while the vertical line represents a comparative value, or target. If the horizontal bar passes the vertical line, the target for that metric has been surpassed. Additionally, the segmented colored sections behind the horizontal bar represent range scores, such as “poor,” “fair,” or “good.”

14. Choropleth Maps

A choropleth map uses color, shading, and other patterns to visualize numerical values across geographic regions. These visualizations use a progression of color (or shading) on a spectrum to distinguish high values from low.

Choropleth maps allow viewers to see how a variable changes from one region to the next. A potential downside to this type of visualization is that the exact numerical values aren’t easily accessible because the colors represent a range of values. Some data visualization tools, however, allow you to add interactivity to your map so the exact values are accessible.

15. Word Cloud

A word cloud , or tag cloud, is a visual representation of text data in which the size of the word is proportional to its frequency. The more often a specific word appears in a dataset, the larger it appears in the visualization. In addition to size, words often appear bolder or follow a specific color scheme depending on their frequency.

Word clouds are often used on websites and blogs to identify significant keywords and compare differences in textual data between two sources. They are also useful when analyzing qualitative datasets, such as the specific words consumers used to describe a product.

16. Network Diagram

Network diagrams are a type of data visualization that represent relationships between qualitative data points. These visualizations are composed of nodes and links, also called edges. Nodes are singular data points that are connected to other nodes through edges, which show the relationship between multiple nodes.

There are many use cases for network diagrams, including depicting social networks, highlighting the relationships between employees at an organization, or visualizing product sales across geographic regions.

17. Correlation Matrix

A correlation matrix is a table that shows correlation coefficients between variables. Each cell represents the relationship between two variables, and a color scale is used to communicate whether the variables are correlated and to what extent.

Correlation matrices are useful to summarize and find patterns in large data sets. In business, a correlation matrix might be used to analyze how different data points about a specific product might be related, such as price, advertising spend, launch date, etc.

Other Data Visualization Options

While the examples listed above are some of the most commonly used techniques, there are many other ways you can visualize data to become a more effective communicator. Some other data visualization options include:

• Bubble clouds
• Circle views
• Dendrograms
• Dot distribution maps
• Open-high-low-close charts
• Polar areas
• Radial trees
• Ring Charts
• Sankey diagram
• Span charts
• Streamgraphs
• Wedge stack graphs
• Violin plots

Tips For Creating Effective Visualizations

Creating effective data visualizations requires more than just knowing how to choose the best technique for your needs. There are several considerations you should take into account to maximize your effectiveness when it comes to presenting data.

Related : What to Keep in Mind When Creating Data Visualizations in Excel

One of the most important steps is to evaluate your audience. For example, if you’re presenting financial data to a team that works in an unrelated department, you’ll want to choose a fairly simple illustration. On the other hand, if you’re presenting financial data to a team of finance experts, it’s likely you can safely include more complex information.

Another helpful tip is to avoid unnecessary distractions. Although visual elements like animation can be a great way to add interest, they can also distract from the key points the illustration is trying to convey and hinder the viewer’s ability to quickly understand the information.

Finally, be mindful of the colors you utilize, as well as your overall design. While it’s important that your graphs or charts are visually appealing, there are more practical reasons you might choose one color palette over another. For instance, using low contrast colors can make it difficult for your audience to discern differences between data points. Using colors that are too bold, however, can make the illustration overwhelming or distracting for the viewer.

Related : Bad Data Visualization: 5 Examples of Misleading Data

Visuals to Interpret and Share Information

No matter your role or title within an organization, data visualization is a skill that’s important for all professionals. Being able to effectively present complex data through easy-to-understand visual representations is invaluable when it comes to communicating information with members both inside and outside your business.

There’s no shortage in how data visualization can be applied in the real world. Data is playing an increasingly important role in the marketplace today, and data literacy is the first step in understanding how analytics can be used in business.

Are you interested in improving your analytical skills? Learn more about Business Analytics , our eight-week online course that can help you use data to generate insights and tackle business decisions.

This post was updated on January 20, 2022. It was originally published on September 17, 2019.

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Present Your Data Like a Pro

• Joel Schwartzberg

Demystify the numbers. Your audience will thank you.

While a good presentation has data, data alone doesn’t guarantee a good presentation. It’s all about how that data is presented. The quickest way to confuse your audience is by sharing too many details at once. The only data points you should share are those that significantly support your point — and ideally, one point per chart. To avoid the debacle of sheepishly translating hard-to-see numbers and labels, rehearse your presentation with colleagues sitting as far away as the actual audience would. While you’ve been working with the same chart for weeks or months, your audience will be exposed to it for mere seconds. Give them the best chance of comprehending your data by using simple, clear, and complete language to identify X and Y axes, pie pieces, bars, and other diagrammatic elements. Try to avoid abbreviations that aren’t obvious, and don’t assume labeled components on one slide will be remembered on subsequent slides. Every valuable chart or pie graph has an “Aha!” zone — a number or range of data that reveals something crucial to your point. Make sure you visually highlight the “Aha!” zone, reinforcing the moment by explaining it to your audience.

With so many ways to spin and distort information these days, a presentation needs to do more than simply share great ideas — it needs to support those ideas with credible data. That’s true whether you’re an executive pitching new business clients, a vendor selling her services, or a CEO making a case for change.

• JS Joel Schwartzberg oversees executive communications for a major national nonprofit, is a professional presentation coach, and is the author of Get to the Point! Sharpen Your Message and Make Your Words Matter and The Language of Leadership: How to Engage and Inspire Your Team . You can find him on LinkedIn and X. TheJoelTruth

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Blog Data Visualization 10 Data Presentation Examples For Strategic Communication

10 Data Presentation Examples For Strategic Communication

Written by: Krystle Wong Sep 28, 2023

Knowing how to present data is like having a superpower. 

Data presentation today is no longer just about numbers on a screen; it’s storytelling with a purpose. It’s about captivating your audience, making complex stuff look simple and inspiring action. 

To help turn your data into stories that stick, influence decisions and make an impact, check out Venngage’s free chart maker or follow me on a tour into the world of data storytelling along with data presentation templates that work across different fields, from business boardrooms to the classroom and beyond. Keep scrolling to learn more! 

Click to jump ahead:

10 Essential data presentation examples + methods you should know

What should be included in a data presentation, what are some common mistakes to avoid when presenting data, faqs on data presentation examples, transform your message with impactful data storytelling.

Data presentation is a vital skill in today’s information-driven world. Whether you’re in business, academia, or simply want to convey information effectively, knowing the different ways of presenting data is crucial. For impactful data storytelling, consider these essential data presentation methods:

1. Bar graph

Ideal for comparing data across categories or showing trends over time.

Bar graphs, also known as bar charts are workhorses of data presentation. They’re like the Swiss Army knives of visualization methods because they can be used to compare data in different categories or display data changes over time. 

In a bar chart, categories are displayed on the x-axis and the corresponding values are represented by the height of the bars on the y-axis. 

It’s a straightforward and effective way to showcase raw data, making it a staple in business reports, academic presentations and beyond.

Make sure your bar charts are concise with easy-to-read labels. Whether your bars go up or sideways, keep it simple by not overloading with too many categories.

2. Line graph

Great for displaying trends and variations in data points over time or continuous variables.

Line charts or line graphs are your go-to when you want to visualize trends and variations in data sets over time.

One of the best quantitative data presentation examples, they work exceptionally well for showing continuous data, such as sales projections over the last couple of years or supply and demand fluctuations. 

The x-axis represents time or a continuous variable and the y-axis represents the data values. By connecting the data points with lines, you can easily spot trends and fluctuations.

A tip when presenting data with line charts is to minimize the lines and not make it too crowded. Highlight the big changes, put on some labels and give it a catchy title.

3. Pie chart

Useful for illustrating parts of a whole, such as percentages or proportions.

Pie charts are perfect for showing how a whole is divided into parts. They’re commonly used to represent percentages or proportions and are great for presenting survey results that involve demographic data. 

Each “slice” of the pie represents a portion of the whole and the size of each slice corresponds to its share of the total. 

While pie charts are handy for illustrating simple distributions, they can become confusing when dealing with too many categories or when the differences in proportions are subtle.

Don’t get too carried away with slices — label those slices with percentages or values so people know what’s what and consider using a legend for more categories.

4. Scatter plot

Effective for showing the relationship between two variables and identifying correlations.

Scatter plots are all about exploring relationships between two variables. They’re great for uncovering correlations, trends or patterns in data. 

In a scatter plot, every data point appears as a dot on the chart, with one variable marked on the horizontal x-axis and the other on the vertical y-axis.

By examining the scatter of points, you can discern the nature of the relationship between the variables, whether it’s positive, negative or no correlation at all.

If you’re using scatter plots to reveal relationships between two variables, be sure to add trendlines or regression analysis when appropriate to clarify patterns. Label data points selectively or provide tooltips for detailed information.

5. Histogram

Best for visualizing the distribution and frequency of a single variable.

Histograms are your choice when you want to understand the distribution and frequency of a single variable. 

They divide the data into “bins” or intervals and the height of each bar represents the frequency or count of data points falling into that interval. 

Histograms are excellent for helping to identify trends in data distributions, such as peaks, gaps or skewness.

Here’s something to take note of — ensure that your histogram bins are appropriately sized to capture meaningful data patterns. Using clear axis labels and titles can also help explain the distribution of the data effectively.

6. Stacked bar chart

Useful for showing how different components contribute to a whole over multiple categories.

Stacked bar charts are a handy choice when you want to illustrate how different components contribute to a whole across multiple categories. 

Each bar represents a category and the bars are divided into segments to show the contribution of various components within each category. 

This method is ideal for highlighting both the individual and collective significance of each component, making it a valuable tool for comparative analysis.

Stacked bar charts are like data sandwiches—label each layer so people know what’s what. Keep the order logical and don’t forget the paintbrush for snazzy colors. Here’s a data analysis presentation example on writers’ productivity using stacked bar charts:

7. Area chart

Similar to line charts but with the area below the lines filled, making them suitable for showing cumulative data.

Area charts are close cousins of line charts but come with a twist. 

Imagine plotting the sales of a product over several months. In an area chart, the space between the line and the x-axis is filled, providing a visual representation of the cumulative total. 

This makes it easy to see how values stack up over time, making area charts a valuable tool for tracking trends in data.

For area charts, use them to visualize cumulative data and trends, but avoid overcrowding the chart. Add labels, especially at significant points and make sure the area under the lines is filled with a visually appealing color gradient.

8. Tabular presentation

Presenting data in rows and columns, often used for precise data values and comparisons.

Tabular data presentation is all about clarity and precision. Think of it as presenting numerical data in a structured grid, with rows and columns clearly displaying individual data points. 

A table is invaluable for showcasing detailed data, facilitating comparisons and presenting numerical information that needs to be exact. They’re commonly used in reports, spreadsheets and academic papers.

When presenting tabular data, organize it neatly with clear headers and appropriate column widths. Highlight important data points or patterns using shading or font formatting for better readability.

9. Textual data

Utilizing written or descriptive content to explain or complement data, such as annotations or explanatory text.

Textual data presentation may not involve charts or graphs, but it’s one of the most used qualitative data presentation examples. 

It involves using written content to provide context, explanations or annotations alongside data visuals. Think of it as the narrative that guides your audience through the data. 

Well-crafted textual data can make complex information more accessible and help your audience understand the significance of the numbers and visuals.

Textual data is your chance to tell a story. Break down complex information into bullet points or short paragraphs and use headings to guide the reader’s attention.

10. Pictogram

Using simple icons or images to represent data is especially useful for conveying information in a visually intuitive manner.

Pictograms are all about harnessing the power of images to convey data in an easy-to-understand way. 

Instead of using numbers or complex graphs, you use simple icons or images to represent data points. 

For instance, you could use a thumbs up emoji to illustrate customer satisfaction levels, where each face represents a different level of satisfaction. 

Pictograms are great for conveying data visually, so choose symbols that are easy to interpret and relevant to the data. Use consistent scaling and a legend to explain the symbols’ meanings, ensuring clarity in your presentation.

Looking for more data presentation ideas? Use the Venngage graph maker or browse through our gallery of chart templates to pick a template and get started! 

A comprehensive data presentation should include several key elements to effectively convey information and insights to your audience. Here’s a list of what should be included in a data presentation:

1. Title and objective

• Begin with a clear and informative title that sets the context for your presentation.
• State the primary objective or purpose of the presentation to provide a clear focus.

2. Key data points

• Present the most essential data points or findings that align with your objective.
• Use charts, graphical presentations or visuals to illustrate these key points for better comprehension.

3. Context and significance

• Provide a brief overview of the context in which the data was collected and why it’s significant.
• Explain how the data relates to the larger picture or the problem you’re addressing.

4. Key takeaways

• Summarize the main insights or conclusions that can be drawn from the data.
• Highlight the key takeaways that the audience should remember.

5. Visuals and charts

• Use clear and appropriate visual aids to complement the data.
• Ensure that visuals are easy to understand and support your narrative.

6. Implications or actions

• Discuss the practical implications of the data or any recommended actions.
• If applicable, outline next steps or decisions that should be taken based on the data.

7. Q&A and discussion

• Allocate time for questions and open discussion to engage the audience.
• Address queries and provide additional insights or context as needed.

Presenting data is a crucial skill in various professional fields, from business to academia and beyond. To ensure your data presentations hit the mark, here are some common mistakes that you should steer clear of:

Overloading with data

Presenting too much data at once can overwhelm your audience. Focus on the key points and relevant information to keep the presentation concise and focused. Here are some free data visualization tools you can use to convey data in an engaging and impactful way. 

Assuming everyone’s on the same page

It’s easy to assume that your audience understands as much about the topic as you do. But this can lead to either dumbing things down too much or diving into a bunch of jargon that leaves folks scratching their heads. Take a beat to figure out where your audience is coming from and tailor your presentation accordingly.

Misleading visuals

Using misleading visuals, such as distorted scales or inappropriate chart types can distort the data’s meaning. Pick the right data infographics and understandable charts to ensure that your visual representations accurately reflect the data.

Not providing context

Data without context is like a puzzle piece with no picture on it. Without proper context, data may be meaningless or misinterpreted. Explain the background, methodology and significance of the data.

Not citing sources properly

Neglecting to cite sources and provide citations for your data can erode its credibility. Always attribute data to its source and utilize reliable sources for your presentation.

Not telling a story

Avoid simply presenting numbers. If your presentation lacks a clear, engaging story that takes your audience on a journey from the beginning (setting the scene) through the middle (data analysis) to the end (the big insights and recommendations), you’re likely to lose their interest.

Infographics are great for storytelling because they mix cool visuals with short and sweet text to explain complicated stuff in a fun and easy way. Create one with Venngage’s free infographic maker to create a memorable story that your audience will remember.

Ignoring data quality

Presenting data without first checking its quality and accuracy can lead to misinformation. Validate and clean your data before presenting it.

Simplify your visuals

Fancy charts might look cool, but if they confuse people, what’s the point? Go for the simplest visual that gets your message across. Having a dilemma between presenting data with infographics v.s data design? This article on the difference between data design and infographics might help you out. 

Missing the emotional connection

Data isn’t just about numbers; it’s about people and real-life situations. Don’t forget to sprinkle in some human touch, whether it’s through relatable stories, examples or showing how the data impacts real lives.

Skipping the actionable insights

At the end of the day, your audience wants to know what they should do with all the data. If you don’t wrap up with clear, actionable insights or recommendations, you’re leaving them hanging. Always finish up with practical takeaways and the next steps.

Can you provide some data presentation examples for business reports?

Business reports often benefit from data presentation through bar charts showing sales trends over time, pie charts displaying market share,or tables presenting financial performance metrics like revenue and profit margins.

What are some creative data presentation examples for academic presentations?

Creative data presentation ideas for academic presentations include using statistical infographics to illustrate research findings and statistical data, incorporating storytelling techniques to engage the audience or utilizing heat maps to visualize data patterns.

What are the key considerations when choosing the right data presentation format?

When choosing a chart format , consider factors like data complexity, audience expertise and the message you want to convey. Options include charts (e.g., bar, line, pie), tables, heat maps, data visualization infographics and interactive dashboards.

Knowing the type of data visualization that best serves your data is just half the battle. Here are some best practices for data visualization to make sure that the final output is optimized. 

How can I choose the right data presentation method for my data?

To select the right data presentation method, start by defining your presentation’s purpose and audience. Then, match your data type (e.g., quantitative, qualitative) with suitable visualization techniques (e.g., histograms, word clouds) and choose an appropriate presentation format (e.g., slide deck, report, live demo).

For more presentation ideas , check out this guide on how to make a good presentation or use a presentation software to simplify the process.  

How can I make my data presentations more engaging and informative?

To enhance data presentations, use compelling narratives, relatable examples and fun data infographics that simplify complex data. Encourage audience interaction, offer actionable insights and incorporate storytelling elements to engage and inform effectively.

The opening of your presentation holds immense power in setting the stage for your audience. To design a presentation and convey your data in an engaging and informative, try out Venngage’s free presentation maker to pick the right presentation design for your audience and topic. 

What is the difference between data visualization and data presentation?

Data presentation typically involves conveying data reports and insights to an audience, often using visuals like charts and graphs. Data visualization , on the other hand, focuses on creating those visual representations of data to facilitate understanding and analysis. 

Now that you’ve learned a thing or two about how to use these methods of data presentation to tell a compelling data story , it’s time to take these strategies and make them your own. 

But here’s the deal: these aren’t just one-size-fits-all solutions. Remember that each example we’ve uncovered here is not a rigid template but a source of inspiration. It’s all about making your audience go, “Wow, I get it now!”

Think of your data presentations as your canvas – it’s where you paint your story, convey meaningful insights and make real change happen. 

So, go forth, present your data with confidence and purpose and watch as your strategic influence grows, one compelling presentation at a time.

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Many people find frequency tables, crosstabs, and other forms of numerical statistical results intimidating. The same information can usually be presented in graphical form, which makes it easier to understand and less intimidating. Graphs tell a story with visuals rather than in words or numbers and can help readers understand the substance of the findings rather than the technical details behind the numbers.

There are numerous graphing options when it comes to presenting data. Here we will take a look at the most popularly used: pie charts , bar graphs , statistical maps, histograms, and frequency polygons.

A pie chart is a graph that shows the differences in frequencies or percentages among categories of a nominal or ordinal variable. The categories are displayed as segments of a circle whose pieces add up to 100 percent of the total frequencies.

Pie charts are a great way to graphically show a frequency distribution. In a pie chart, the frequency or percentage is represented both visually and numerically, so it is typically quick for readers to understand the data and what the researcher is conveying.

Like a pie chart, a bar graph is also a way to visually show the differences in frequencies or percentages among categories of a nominal or ordinal variable. In a bar graph, however, the categories are displayed as rectangles of equal width with their height proportional to the frequency of percentage of the category.

Unlike pie charts, bar graphs are very useful for comparing categories of a variable among different groups. For example, we can compare marital status among U.S. adults by gender. This graph would, thus, have two bars for each category of marital status: one for males and one for females. The pie chart does not allow you to include more than one group. You would have to create two separate pie charts, one for females and one for males.

Statistical Maps

Statistical maps are a way to display the geographic distribution of data. For example, let’s say we are studying the geographic distribution of the elderly persons in the United States. A statistical map would be a great way to visually display our data. On our map, each category is represented by a different color or shade and the states are then shaded depending on their classification into the different categories.

In our example of the elderly in the United States, let’s say we had four categories, each with its own color: Less than 10 percent (red), 10 to 11.9 percent (yellow), 12 to 13.9 percent (blue), and 14 percent or more (green). If 12.2 percent of Arizona’s population is over 65 years old, Arizona would be shaded blue on our map. Likewise, if Florida’s has 15 percent of its population aged 65 and older, it would be shaded green on the map.

Maps can display geographical data on the level of cities, counties, city blocks, census tracts, countries, states, or other units. This choice depends on the researcher’s topic and the questions they are exploring.

A histogram is used to show the differences in frequencies or percentages among categories of an interval-ratio variable. The categories are displayed as bars, with the width of the bar proportional to the width of the category and the height proportional to the frequency or percentage of that category. The area that each bar occupies on a histogram tells us the proportion of the population that falls into a given interval. A histogram looks very similar to a bar chart, however, in a histogram, the bars are touching and may not be of equal width. In a bar chart, the space between the bars indicates that the categories are separate.

Whether a researcher creates a bar chart or a histogram depends on the type of data he or she is using. Typically, bar charts are created with qualitative data (nominal or ordinal variables) while histograms are created with quantitative data (interval-ratio variables).

Frequency Polygons

A frequency polygon is a graph showing the differences in frequencies or percentages among categories of an interval-ratio variable. Points representing the frequencies of each category are placed above the midpoint of the category and are joined by a straight line. A frequency polygon is similar to a histogram, however, instead of bars, a point is used to show the frequency and all the points are then connected with a line.

Distortions in Graphs

When a graph is distorted, it can quickly deceive the reader into thinking something other than what the data really says. There are several ways that graphs can be distorted.

Probably the most common way that graphs get distorted is when the distance along the vertical or horizontal axis is altered in relation to the other axis. Axes can be stretched or shrunk to create any desired result. For example, if you were to shrink the horizontal axis (X axis), it could make the slope of your line graph appear steeper than it actually is, giving the impression that the results are more dramatic than they are. Likewise, if you expanded the horizontal axis while keeping the vertical axis (Y axis) the same, the slope of the line graph would be more gradual, making the results appear less significant than they really are.

When creating and editing graphs, it is important to make sure the graphs do not get distorted. Oftentimes, it can happen by accident when editing the range of numbers in an axis, for example. Therefore it is important to pay attention to how the data comes across in the graphs and make sure the results are being presented accurately and appropriately, so as to not deceive the readers.

Resources and Further Reading

• Frankfort-Nachmias, Chava, and Anna Leon-Guerrero. Social Statistics for a Diverse Society . SAGE, 2018.
• 7 Graphs Commonly Used in Statistics
• What Is a Bar Graph?
• How Bar Graphs Are Used to Display Data
• What Is a Histogram?
• Relative Frequency Histograms
• Make a Histogram in 7 Simple Steps
• Lesson Plan: Survey Data and Graphing
• What Are Pie Charts and Why Are They Useful?
• What Is a Two-Way Table of Categorical Variables?
• Frequencies and Relative Frequencies
• How and When to Use a Circle or Pie Graph
• Histogram Classes
• How to Discuss Charts and Graphs in English
• Graphing and Data Interpretation Worksheets
• Using Links to Create Vertical Navigation Menus
• What Are Time Series Graphs?

How to develop a graphical framework to chart your research

Graphic representations or frameworks can be powerful tools to explain research processes and outcomes. David Waller explains how researchers can develop effective visual models to chart their work

David Waller

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While undertaking a study, researchers can uncover insights, connections and findings that are extremely valuable to anyone likely to read their eventual paper. Thus, it is important for the researcher to clearly present and explain the ideas and potential relationships. One important way of presenting findings and relationships is by developing a graphical conceptual framework.

A graphical conceptual framework is a visual model that assists readers by illustrating how concepts, constructs, themes or processes work. It is an image designed to help the viewer understand how various factors interrelate and affect outcomes, such as a chart, graph or map.

These are commonly used in research to show outcomes but also to create, develop, test, support and criticise various ideas and models. The use of a conceptual framework can vary depending on whether it is being used for qualitative or quantitative research.

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There are many forms that a graphical conceptual framework can take, which can depend on the topic, the type of research or findings, and what can best present the story.

Below are examples of frameworks based on qualitative and quantitative research.

As shown by the table below, in qualitative research the conceptual framework is developed at the end of the study to illustrate the factors or issues presented in the qualitative data. It is designed to assist in theory building and the visual understanding of the exploratory findings. It can also be used to develop a framework in preparation for testing the proposition using quantitative research.

In quantitative research a conceptual framework can be used to synthesise the literature and theoretical concepts at the beginning of the study to present a model that will be tested in the statistical analysis of the research.

It is important to understand that the role of a conceptual framework differs depending on the type of research that is being undertaken.

So how should you go about creating a conceptual framework? After undertaking some studies where I have developed conceptual frameworks, here is a simple model based on “Six Rs”: Review, Reflect, Relationships, Reflect, Review, and Repeat.

Process for developing conceptual frameworks:

Review: literature/themes/theory.

Reflect: what are the main concepts/issues?

Relationships: what are their relationships?

Reflect: does the diagram represent it sufficiently?

Review: check it with theory, colleagues, stakeholders, etc.

Repeat: review and revise it to see if something better occurs.

This is not an easy process. It is important to begin by reviewing what has been presented in previous studies in the literature or in practice. This provides a solid background to the proposed model as it can show how it relates to accepted theoretical concepts or practical examples, and helps make sure that it is grounded in logical sense.

It can start with pen and paper, but after reviewing you should reflect to consider if the proposed framework takes into account the main concepts and issues, and the potential relationships that have been presented on the topic in previous works.

It may take a few versions before you are happy with the final framework, so it is worth continuing to reflect on the model and review its worth by reassessing it to determine if the model is consistent with the literature and theories. It can also be useful to discuss the idea with  colleagues or to present preliminary ideas at a conference or workshop –  be open to changes.

Even after you come up with a potential model it is good to repeat the process to review the framework and be prepared to revise it as this can help in refining the model. Over time you may develop a number of models with each one superseding the previous one.

A concern is that some students hold on to the framework they first thought of and worry that developing or changing it will be seen as a weakness in their research. However, a revised and refined model can be an important factor in justifying the value of the research.

Plenty of possibilities and theoretical topics could be considered to enhance the model. Whether it ultimately supports the theoretical constructs of the research will be dependent on what occurs when it is tested.  As social psychologist, Kurt Lewin, famously said “ There's nothing so practical as good theory ”.

The final result after doing your reviewing and reflecting should be a clear graphical presentation that will help the reader understand what the research is about as well as where it is heading.

It doesn’t need to be complex. A simple diagram or table can clarify the nature of a process and help in its analysis, which can be important for the researcher when communicating to their audience. As the saying goes: “ A picture is worth 1000 words ”. The same goes for a good conceptual framework, when explaining a research process or findings.

David Waller is an associate professor at the University of Technology Sydney .

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by Tom Rielly • May 12, 2020

When giving presentations, either on a video conference call or in person, your slides, videos and graphics (or lack of them) can be an important element in helping you tell your story or express your idea. This is the first of a series of blog posts that will give you tips and tricks on how to perfect your visual presentations.

Your job as a presenter is to build your idea -- step-by-step -- in the minds of your audience members. One tool to do that is presentation graphics, such as slides and videos.

Why graphics for your presentation?

A common mistake is using slides or videos as a crutch, even if they don’t actually add anything to your presentation. Not all presentations need graphics. Lots of presentations work wonderfully with just one person standing on a stage telling a story, as demonstrated by many TED Talks.

You should only use slides if they serve a purpose: conveying scientific information, art, and things that are hard to explain without pictures. Once you have decided on using slides, you will have a number of decisions to make. We’ll help you with the basics of making a presentation that is, above all, clear and easy to understand. The most important thing to remember here is: less is more.

Less is so much more

You want to aim for the fewest number of slides, the fewest number of photos, the fewest words per slide, the least cluttered slides and the most white space on your slides. This is the most violated slide rule, but it is the secret to success. Take a look at these examples.

As you can see in the above example, you don’t need fancy backgrounds or extra words to convey a simple concept. If you take “Everything you need to know about Turtles”, and delete “everything you need to know about” leaving just “turtles”, the slide has become much easier for your audience to read, and tells the story with economy.

The above example demonstrates that a single image that fills the entire screen is far more powerful than a slide cluttered with images. A slide with too many images may be detrimental to your presentation. The audience will spend more mental energy trying to sort through the clutter than listening to your presentation. If you need multiple images, then put each one on its own slide. Make each image high-resolution and have it fill the entire screen. If the photos are not the same dimensions as the screen, put them on a black background. Don’t use other colors, especially white.

Your slides will be much more effective if you use the fewest words, characters, and pictures needed to tell your story. Long paragraphs make the audience strain to read them, which means they are not paying attention to you. Your audience may even get stressed if you move on to your next slide before they’ve finished reading your paragraph. The best way to make sure the attention stays on you is to limit word count to no more than 10 words per slide. As presentation expert Nancy Duarte says “any slide with more than 10 words is a document.” If you really do need a longer explanation of something, handouts or follow-up emails are the way to go.

Following a “less is more” approach is one of the simplest things you can do to improve your presentation visuals and the impact of your presentation overall. Make sure your visuals add to your presentation rather than distract from it and get your message across.

Ready to learn more about how to make your presentation even better? Get TED Masterclass and develop your ideas into TED-style talks.

© 2024 TED Conferences, LLC. All rights reserved. Please note that the TED Talks Usage policy does not apply to this content and is not subject to our creative commons license.

Graphic Presentation of Data

• First Online: 24 August 2018

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• Charan Singh Rayat 2  

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Graphic presentation is considered the preferred way of presentation of data over diagrammatic presentation as graphs are always more accurate and precise, whereas diagrams are generally used for the purpose of publicity and propaganda. Relationship between two variables can be studied by graphs. These can be drawn more easily than diagrams. Graphs are considered very useful for studying time series and frequency distribution.

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Rayat, C.S. (2018). Graphic Presentation of Data. In: Statistical Methods in Medical Research. Springer, Singapore. https://doi.org/10.1007/978-981-13-0827-7_5

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• Graphic Presentation of Data

Apart from diagrams, Graphic presentation is another way of the presentation of data and information. Usually, graphs are used to present time series and frequency distributions. In this article, we will look at the graphic presentation of data and information along with its merits, limitations , and types.

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Construction of a graph.

The graphic presentation of data and information offers a quick and simple way of understanding the features and drawing comparisons. Further, it is an effective analytical tool and a graph can help us in finding the mode, median, etc.

We can locate a point in a plane using two mutually perpendicular lines – the X-axis (the horizontal line) and the Y-axis (the vertical line). Their point of intersection is the Origin .

We can locate the position of a point in terms of its distance from both these axes. For example, if a point P is 3 units away from the Y-axis and 5 units away from the X-axis, then its location is as follows:

Browse more Topics under Descriptive Statistics

• Definition and Characteristics of Statistics
• Stages of Statistical Enquiry
• Importance and Functions of Statistics
• Nature of Statistics – Science or Art?
• Application of Statistics
• Law of Statistics and Distrust of Statistics
• Meaning and Types of Data
• Methods of Collecting Data
• Sample Investigation
• Classification of Data
• Tabulation of Data
• Frequency Distribution of Data
• Diagrammatic Presentation of Data
• Measures of Central Tendency
• Mean Median Mode
• Measures of Dispersion
• Standard Deviation
• Variance Analysis

Some points to remember:

• We measure the distance of the point from the Y-axis along the X-axis. Similarly, we measure the distance of the point from the X-axis along the Y-axis. Therefore, to measure 3 units from the Y-axis, we move 3 units along the X-axis and likewise for the other coordinate .
• We then draw perpendicular lines from these two points.
• The point where the perpendiculars intersect is the position of the point P.
• We denote it as follows (3,5) or (abscissa, ordinate). Together, they are the coordinates of the point P.
• The four parts of the plane are Quadrants.
• Also, we can plot different points for a different pair of values.

General Rules for Graphic Presentation of Data and Information

There are certain guidelines for an attractive and effective graphic presentation of data and information. These are as follows:

• Suitable Title – Ensure that you give a suitable title to the graph which clearly indicates the subject for which you are presenting it.
• Unit of Measurement – Clearly state the unit of measurement below the title.
• Suitable Scale – Choose a suitable scale so that you can represent the entire data in an accurate manner.
• Index – Include a brief index which explains the different colors and shades, lines and designs that you have used in the graph. Also, include a scale of interpretation for better understanding.
• Data Sources – Wherever possible, include the sources of information at the bottom of the graph.
• Keep it Simple – You should construct a graph which even a layman (without any exposure in the areas of statistics or mathematics) can understand.
• Neat – A graph is a visual aid for the presentation of data and information. Therefore, you must keep it neat and attractive. Choose the right size, right lettering, and appropriate lines, colors, dashes, etc.

Merits of a Graph

• The graph presents data in a manner which is easier to understand.
• It allows us to present statistical data in an attractive manner as compared to tables. Users can understand the main features, trends, and fluctuations of the data at a glance.
• A graph saves time.
• It allows the viewer to compare data relating to two different time-periods or regions.
• The viewer does not require prior knowledge of mathematics or statistics to understand a graph.
• We can use a graph to locate the mode, median, and mean values of the data.
• It is useful in forecasting, interpolation, and extrapolation of data.

Limitations of a Graph

• A graph lacks complete accuracy of facts.
• It depicts only a few selected characteristics of the data.
• We cannot use a graph in support of a statement.
• A graph is not a substitute for tables.
• Usually, laymen find it difficult to understand and interpret a graph.
• Typically, a graph shows the unreasonable tendency of the data and the actual values are not clear.

Types of Graphs

Graphs are of two types:

• Time Series graphs
• Frequency Distribution graphs

Time Series Graphs

A time series graph or a “ histogram ” is a graph which depicts the value of a variable over a different point of time. In a time series graph, time is the most important factor and the variable is related to time. It helps in the understanding and analysis of the changes in the variable at a different point of time. Many statisticians and businessmen use these graphs because they are easy to understand and also because they offer complex information in a simple manner.

Further, constructing a time series graph does not require a user with technical skills. Here are some major steps in the construction of a time series graph:

• Represent time on the X-axis and the value of the variable on the Y-axis.
• Start the Y-value with zero and devise a suitable scale which helps you present the whole data in the given space.
• Plot the values of the variable and join different point with a straight line.
• You can plot multiple variables through different lines.

You can use a line graph to summarize how two pieces of information are related and how they vary with each other.

• You can compare multiple continuous data-sets easily
• You can infer the interim data from the graph line

Disadvantages

• It is only used with continuous data.

Use of a false Base Line

Usually, in a graph, the vertical line starts from the Origin. However, in some cases, a false Base Line is used for a better representation of the data. There are two scenarios where you should use a false Base Line:

• To magnify the minor fluctuation in the time series data
• To economize the space

Net Balance Graph

If you have to show the net balance of income and expenditure or revenue and costs or imports and exports, etc., then you must use a net balance graph. You can use different colors or shades for positive and negative differences.

Frequency Distribution Graphs

Let’s look at the different types of frequency distribution graphs.

A histogram is a graph of a grouped frequency distribution. In a histogram, we plot the class intervals on the X-axis and their respective frequencies on the Y-axis. Further, we create a rectangle on each class interval with its height proportional to the frequency density of the class.

Frequency Polygon or Histograph

A frequency polygon or a Histograph is another way of representing a frequency distribution on a graph. You draw a frequency polygon by joining the midpoints of the upper widths of the adjacent rectangles of the histogram with straight lines.

Frequency Curve

When you join the verticals of a polygon using a smooth curve, then the resulting figure is a Frequency Curve. As the number of observations increase, we need to accommodate more classes. Therefore, the width of each class reduces. In such a scenario, the variable tends to become continuous and the frequency polygon starts taking the shape of a frequency curve.

Cumulative Frequency Curve or Ogive

A cumulative frequency curve or Ogive is the graphical representation of a cumulative frequency distribution. Since a cumulative frequency is either of a ‘less than’ or a ‘more than’ type, Ogives are of two types too – ‘less than ogive’ and ‘more than ogive’.

Scatter Diagram

A scatter diagram or a dot chart enables us to find the nature of the relationship between the variables. If the plotted points are scattered a lot, then the relationship between the two variables is lesser.

Solved Question

Q1. What are the general rules for the graphic presentation of data and information?

Answer: The general rules for the graphic presentation of data are:

• Use a suitable title
• Clearly specify the unit of measurement
• Ensure that you choose a suitable scale
• Provide an index specifying the colors, lines, and designs used in the graph
• If possible, provide the sources of information at the bottom of the graph
• Keep the graph simple and neat.

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Presentation of Data

Statistics deals with the collection, presentation and analysis of the data, as well as drawing meaningful conclusions from the given data. Generally, the data can be classified into two different types, namely primary data and secondary data. If the information is collected by the investigator with a definite objective in their mind, then the data obtained is called the primary data. If the information is gathered from a source, which already had the information stored, then the data obtained is called secondary data. Once the data is collected, the presentation of data plays a major role in concluding the result. Here, we will discuss how to present the data with many solved examples.

What is Meant by Presentation of Data?

As soon as the data collection is over, the investigator needs to find a way of presenting the data in a meaningful, efficient and easily understood way to identify the main features of the data at a glance using a suitable presentation method. Generally, the data in the statistics can be presented in three different forms, such as textual method, tabular method and graphical method.

Presentation of Data Examples

Now, let us discuss how to present the data in a meaningful way with the help of examples.

Consider the marks given below, which are obtained by 10 students in Mathematics:

36, 55, 73, 95, 42, 60, 78, 25, 62, 75.

Find the range for the given data.

Given Data: 36, 55, 73, 95, 42, 60, 78, 25, 62, 75.

The data given is called the raw data.

First, arrange the data in the ascending order : 25, 36, 42, 55, 60, 62, 73, 75, 78, 95.

Therefore, the lowest mark is 25 and the highest mark is 95.

We know that the range of the data is the difference between the highest and the lowest value in the dataset.

Therefore, Range = 95-25 = 70.

Note: Presentation of data in ascending or descending order can be time-consuming if we have a larger number of observations in an experiment.

Now, let us discuss how to present the data if we have a comparatively more number of observations in an experiment.

Consider the marks obtained by 30 students in Mathematics subject (out of 100 marks)

10, 20, 36, 92, 95, 40, 50, 56, 60, 70, 92, 88, 80, 70, 72, 70, 36, 40, 36, 40, 92, 40, 50, 50, 56, 60, 70, 60, 60, 88.

In this example, the number of observations is larger compared to example 1. So, the presentation of data in ascending or descending order is a bit time-consuming. Hence, we can go for the method called ungrouped frequency distribution table or simply frequency distribution table . In this method, we can arrange the data in tabular form in terms of frequency.

For example, 3 students scored 50 marks. Hence, the frequency of 50 marks is 3. Now, let us construct the frequency distribution table for the given data.

Therefore, the presentation of data is given as below:

The following example shows the presentation of data for the larger number of observations in an experiment.

Consider the marks obtained by 100 students in a Mathematics subject (out of 100 marks)

95, 67, 28, 32, 65, 65, 69, 33, 98, 96,76, 42, 32, 38, 42, 40, 40, 69, 95, 92, 75, 83, 76, 83, 85, 62, 37, 65, 63, 42, 89, 65, 73, 81, 49, 52, 64, 76, 83, 92, 93, 68, 52, 79, 81, 83, 59, 82, 75, 82, 86, 90, 44, 62, 31, 36, 38, 42, 39, 83, 87, 56, 58, 23, 35, 76, 83, 85, 30, 68, 69, 83, 86, 43, 45, 39, 83, 75, 66, 83, 92, 75, 89, 66, 91, 27, 88, 89, 93, 42, 53, 69, 90, 55, 66, 49, 52, 83, 34, 36.

Now, we have 100 observations to present the data. In this case, we have more data when compared to example 1 and example 2. So, these data can be arranged in the tabular form called the grouped frequency table. Hence, we group the given data like 20-29, 30-39, 40-49, ….,90-99 (As our data is from 23 to 98). The grouping of data is called the “class interval” or “classes”, and the size of the class is called “class-size” or “class-width”.

In this case, the class size is 10. In each class, we have a lower-class limit and an upper-class limit. For example, if the class interval is 30-39, the lower-class limit is 30, and the upper-class limit is 39. Therefore, the least number in the class interval is called the lower-class limit and the greatest limit in the class interval is called upper-class limit.

Hence, the presentation of data in the grouped frequency table is given below:

Hence, the presentation of data in this form simplifies the data and it helps to enable the observer to understand the main feature of data at a glance.

Practice Problems

• The heights of 50 students (in cms) are given below. Present the data using the grouped frequency table by taking the class intervals as 160 -165, 165 -170, and so on.  Data: 161, 150, 154, 165, 168, 161, 154, 162, 150, 151, 162, 164, 171, 165, 158, 154, 156, 172, 160, 170, 153, 159, 161, 170, 162, 165, 166, 168, 165, 164, 154, 152, 153, 156, 158, 162, 160, 161, 173, 166, 161, 159, 162, 167, 168, 159, 158, 153, 154, 159.
• Three coins are tossed simultaneously and each time the number of heads occurring is noted and it is given below. Present the data using the frequency distribution table. Data: 0, 1, 2, 2, 1, 2, 3, 1, 3, 0, 1, 3, 1, 1, 2, 2, 0, 1, 2, 1, 3, 0, 0, 1, 1, 2, 3, 2, 2, 0.

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• Accountancy
• Business Studies
• Commercial Law
• Organisational Behaviour
• Human Resource Management
• Entrepreneurship
• CBSE Class 11 Statistics for Economics Notes

Chapter 1: Concept of Economics and Significance of Statistics in Economics

• Statistics for Economics | Functions, Importance, and Limitations

Chapter 2: Collection of Data

• Data Collection & Its Methods
• Sources of Data Collection | Primary and Secondary Sources
• Direct Personal Investigation: Meaning, Suitability, Merits, Demerits and Precautions
• Indirect Oral Investigation : Suitability, Merits, Demerits and Precautions
• Difference between Direct Personal Investigation and Indirect Oral Investigation
• Information from Local Source or Correspondents: Meaning, Suitability, Merits, and Demerits
• Questionnaires and Schedules Method of Data Collection
• Difference between Questionnaire and Schedule
• Qualities of a Good Questionnaire and types of Questions
• What are the Published Sources of Collecting Secondary Data?
• What Precautions should be taken before using Secondary Data?
• Two Important Sources of Secondary Data: Census of India and Reports & Publications of NSSO
• What is National Sample Survey Organisation (NSSO)?
• What is Census Method of Collecting Data?
• Sample Method of Collection of Data
• Methods of Sampling
• Father of Indian Census
• What makes a Sampling Data Reliable?
• Difference between Census Method and Sampling Method of Collecting Data
• What are Statistical Errors?

Chapter 3: Organisation of Data

• Organization of Data
• Objectives and Characteristics of Classification of Data
• Classification of Data in Statistics | Meaning and Basis of Classification of Data
• Concept of Variable and Raw Data
• Types of Statistical Series
• Difference between Frequency Array and Frequency Distribution
• Types of Frequency Distribution

Chapter 4: Presentation of Data: Textual and Tabular

• Textual Presentation of Data: Meaning, Suitability, and Drawbacks
• Tabular Presentation of Data: Meaning, Objectives, Features and Merits
• Different Types of Tables
• Classification and Tabulation of Data

Chapter 5: Diagrammatic Presentation of Data

• Diagrammatic Presentation of Data: Meaning , Features, Guidelines, Advantages and Disadvantages
• Types of Diagrams
• Bar Graph | Meaning, Types, and Examples
• Pie Diagrams | Meaning, Example and Steps to Construct
• Histogram | Meaning, Example, Types and Steps to Draw
• Frequency Polygon | Meaning, Steps to Draw and Examples
• Ogive (Cumulative Frequency Curve) and its Types
• What is Arithmetic Line-Graph or Time-Series Graph?

Diagrammatic and Graphic Presentation of Data

Chapter 6: measures of central tendency: arithmetic mean.

• Measures of Central Tendency in Statistics
• Arithmetic Mean: Meaning, Example, Types, Merits, and Demerits
• What is Simple Arithmetic Mean?
• Calculation of Mean in Individual Series | Formula of Mean
• Calculation of Mean in Discrete Series | Formula of Mean
• Calculation of Mean in Continuous Series | Formula of Mean
• Calculation of Arithmetic Mean in Special Cases
• Weighted Arithmetic Mean

Chapter 7: Measures of Central Tendency: Median and Mode

• Median(Measures of Central Tendency): Meaning, Formula, Merits, Demerits, and Examples
• Calculation of Median for Different Types of Statistical Series
• Calculation of Median in Individual Series | Formula of Median
• Calculation of Median in Discrete Series | Formula of Median
• Calculation of Median in Continuous Series | Formula of Median
• Graphical determination of Median
• Mode: Meaning, Formula, Merits, Demerits, and Examples
• Calculation of Mode in Individual Series | Formula of Mode
• Calculation of Mode in Discrete Series | Formula of Mode
• Grouping Method of Calculating Mode in Discrete Series | Formula of Mode
• Calculation of Mode in Continuous Series | Formula of Mode
• Calculation of Mode in Special Cases
• Calculation of Mode by Graphical Method
• Mean, Median and Mode| Comparison, Relationship and Calculation

Chapter 8: Measures of Dispersion

• Measures of Dispersion | Meaning, Absolute and Relative Measures of Dispersion
• Range | Meaning, Coefficient of Range, Merits and Demerits, Calculation of Range
• Calculation of Range and Coefficient of Range
• Interquartile Range and Quartile Deviation
• Partition Value | Quartiles, Deciles and Percentiles
• Quartile Deviation and Coefficient of Quartile Deviation: Meaning, Formula, Calculation, and Examples
• Quartile Deviation in Discrete Series | Formula, Calculation and Examples
• Quartile Deviation in Continuous Series | Formula, Calculation and Examples
• Mean Deviation: Coefficient of Mean Deviation, Merits, and Demerits
• Calculation of Mean Deviation for different types of Statistical Series
• Mean Deviation from Mean | Individual, Discrete, and Continuous Series
• Mean Deviation from Median | Individual, Discrete, and Continuous Series
• Standard Deviation: Meaning, Coefficient of Standard Deviation, Merits, and Demerits
• Standard Deviation in Individual Series
• Methods of Calculating Standard Deviation in Discrete Series
• Methods of calculation of Standard Deviation in frequency distribution series
• Combined Standard Deviation: Meaning, Formula, and Example
• How to calculate Variance?
• Coefficient of Variation: Meaning, Formula and Examples
• Lorenz Curveb : Meaning, Construction, and Application

Chapter 9: Correlation

• Correlation: Meaning, Significance, Types and Degree of Correlation
• Methods of measurements of Correlation
• Calculation of Correlation with Scattered Diagram
• Spearman's Rank Correlation Coefficient
• Karl Pearson's Coefficient of Correlation
• Karl Pearson's Coefficient of Correlation | Methods and Examples

Chapter 10: Index Number

• Index Number | Meaning, Characteristics, Uses and Limitations
• Methods of Construction of Index Number
• Unweighted or Simple Index Numbers: Meaning and Methods
• Methods of calculating Weighted Index Numbers
• Fisher's Index Number as an Ideal Method
• Fisher's Method of calculating Weighted Index Number
• Paasche's Method of calculating Weighted Index Number
• Laspeyre's Method of calculating Weighted Index Number
• Laspeyre's, Paasche's, and Fisher's Methods of Calculating Index Number
• Consumer Price Index (CPI) or Cost of Living Index Number: Construction of Consumer Price Index|Difficulties and Uses of Consumer Price Index
• Methods of Constructing Consumer Price Index (CPI)
• Wholesale Price Index (WPI) | Meaning, Uses, Merits, and Demerits
• Index Number of Industrial Production : Characteristics, Construction & Example
• Inflation and Index Number

Important Formulas in Statistics for Economics

• Important Formulas in Statistics for Economics | Class 11

Diagrammatic and graphic presentation of data means visual representation of the data. It shows a comparison between two or more sets of data and helps in the presentation of highly complex data in its simplest form. Diagrams and graphs are clear and easy to read and understand. In the diagrammatic presentation of data, bar charts, rectangles, sub-divided rectangles, pie charts, or circle diagrams are used. In the graphic presentation of data, graphs like histograms, frequency polygon, frequency curves, cumulative frequency polygon, and graphs of time series are used.

General Rules for Construction of Diagrammatic and Graphic Presentations: 

1. Chronic Number: Each outline or chart should have a chronic number. It is important to recognize one from the other.

2. Title: A title should be given to each outline or chart. From the title, one can understand what the graph or diagram is. The title ought to be brief and simple. It is normally positioned at the top.

3. Legitimate size and scale: An outline or chart ought to be of ordinary size and drawn with an appropriate scale. The scale in a chart indicates the size of the unit.

4. Neatness: Outlines should be pretty much as straightforward as could be expected. Further, they should be very perfect and clean. They ought to likewise be dropped to check out.

5. File: Each outline or chart should be joined by a record. This outlines various sorts of lines, shades or tones utilized in the graph.

6. Commentary: Commentaries might be given at the lower part of an outline. It explains specific focuses in the chart.

Merits of Diagrammatic and Graphics Presentation:

The fundamental benefits or merits of a diagrammatic and graphical representation of data are as follows:

1. To simplify the data: Outlines and charts present information in a simple manner that can be perceived by anyone without any problem. Huge volume of data can be easily presented using graphs and diagrams.

2. Appealing presentation: Outlines and charts present complex information and data in an understandable and engaging manner and leave a great visual effect. In this way, the diagrammatic and graphical representation of information effectively draws the attention of users.

3. Helps with comparison of data: With the help of outlines and charts, comparison and examination data between various arrangements of information is possible.

4. Helps in forecasting: The diagrammatic and graphical representation of information has past patterns, which helps in forecasting and making various policies for the future.

5. Saves time and labour: Charts and graphs make the complex data into a simple form, which can be easily understood by anyone without having prior knowledge of the data. It gives ready to use information, and the user can use it accordingly. In this way, it saves a lot of time and labour.

6. Universally acceptable: Graphs and diagrams are used in every field and can be easily understood by anyone. Hence they are universally acceptable.

7. Helps in decision making: Diagrams and graphs give the real data about the past patterns, trends, outcomes, etc., which helps in future preparation.

Demerits of Diagrammatic and Graphics Presentation:

The demerits of diagrammatic and graphics presentation of data are as follows:

1. Handle with care: Drawing, surmising and understanding from graphs and diagrams needs proper insight and care. A person with little knowledge of statistics cannot analyze or use the data properly.

2. Specific information: Graphs and diagrams do not depict true or precise information. They are generally founded on approximations. The information provided is limited and specific.

3. Low precision: Graphs and diagrams can give misleading results, as they are mostly based on approximation of data. Personal judgement is used to study or analyze the data, which can make the information biased. Also, data can easily be manipulated.

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2.E: Graphical Representations of Data (Exercises)

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2.2: Stem-and-Leaf Graphs (Stemplots), Line Graphs, and Bar Graphs

Student grades on a chemistry exam were: 77, 78, 76, 81, 86, 51, 79, 82, 84, 99

• Construct a stem-and-leaf plot of the data.
• Are there any potential outliers? If so, which scores are they? Why do you consider them outliers?

The table below contains the 2010 obesity rates in U.S. states and Washington, DC.

• Use a random number generator to randomly pick eight states. Construct a bar graph of the obesity rates of those eight states.
• Construct a bar graph for all the states beginning with the letter "A."
• Construct a bar graph for all the states beginning with the letter "M."
• Number the entries in the table 1–51 (Includes Washington, DC; Numbered vertically)
• Arrow over to PRB
• Press 5:randInt(
• Enter 51,1,8)

Eight numbers are generated (use the right arrow key to scroll through the numbers). The numbers correspond to the numbered states (for this example: {47 21 9 23 51 13 25 4}. If any numbers are repeated, generate a different number by using 5:randInt(51,1)). Here, the states (and Washington DC) are {Arkansas, Washington DC, Idaho, Maryland, Michigan, Mississippi, Virginia, Wyoming}.

Corresponding percents are {30.1, 22.2, 26.5, 27.1, 30.9, 34.0, 26.0, 25.1}.

Figure \(\PageIndex{1}\): (a)

Figure \(\PageIndex{1}\): (b)

Figure \(\PageIndex{1}\): (c)

For each of the following data sets, create a stem plot and identify any outliers.

Exercise 2.2.7

The miles per gallon rating for 30 cars are shown below (lowest to highest).

19, 19, 19, 20, 21, 21, 25, 25, 25, 26, 26, 28, 29, 31, 31, 32, 32, 33, 34, 35, 36, 37, 37, 38, 38, 38, 38, 41, 43, 43

The height in feet of 25 trees is shown below (lowest to highest).

25, 27, 33, 34, 34, 34, 35, 37, 37, 38, 39, 39, 39, 40, 41, 45, 46, 47, 49, 50, 50, 53, 53, 54, 54

The data are the prices of different laptops at an electronics store. Round each value to the nearest ten.

249, 249, 260, 265, 265, 280, 299, 299, 309, 319, 325, 326, 350, 350, 350, 365, 369, 389, 409, 459, 489, 559, 569, 570, 610

The data are daily high temperatures in a town for one month.

61, 61, 62, 64, 66, 67, 67, 67, 68, 69, 70, 70, 70, 71, 71, 72, 74, 74, 74, 75, 75, 75, 76, 76, 77, 78, 78, 79, 79, 95

For the next three exercises, use the data to construct a line graph.

Exercise 2.2.8

In a survey, 40 people were asked how many times they visited a store before making a major purchase. The results are shown in the Table below.

Exercise 2.2.9

In a survey, several people were asked how many years it has been since they purchased a mattress. The results are shown in Table .

Exercise 2.2.10

Several children were asked how many TV shows they watch each day. The results of the survey are shown in the Table below.

Exercise 2.2.11

The students in Ms. Ramirez’s math class have birthdays in each of the four seasons. Table shows the four seasons, the number of students who have birthdays in each season, and the percentage (%) of students in each group. Construct a bar graph showing the number of students.

Using the data from Mrs. Ramirez’s math class supplied in the table above, construct a bar graph showing the percentages.

Exercise 2.2.12

David County has six high schools. Each school sent students to participate in a county-wide science competition. Table shows the percentage breakdown of competitors from each school, and the percentage of the entire student population of the county that goes to each school. Construct a bar graph that shows the population percentage of competitors from each school.

Use the data from the David County science competition supplied in Exercise . Construct a bar graph that shows the county-wide population percentage of students at each school.

2.3: Histograms, Frequency, Polygons, and Time Series Graphs

Suppose that three book publishers were interested in the number of fiction paperbacks adult consumers purchase per month. Each publisher conducted a survey. In the survey, adult consumers were asked the number of fiction paperbacks they had purchased the previous month. The results are as follows:

• Find the relative frequencies for each survey. Write them in the charts.
• Using either a graphing calculator, computer, or by hand, use the frequency column to construct a histogram for each publisher's survey. For Publishers A and B, make bar widths of one. For Publisher C, make bar widths of two.
• In complete sentences, give two reasons why the graphs for Publishers A and B are not identical.
• Would you have expected the graph for Publisher C to look like the other two graphs? Why or why not?
• Make new histograms for Publisher A and Publisher B. This time, make bar widths of two.
• Now, compare the graph for Publisher C to the new graphs for Publishers A and B. Are the graphs more similar or more different? Explain your answer.

Often, cruise ships conduct all on-board transactions, with the exception of gambling, on a cashless basis. At the end of the cruise, guests pay one bill that covers all onboard transactions. Suppose that 60 single travelers and 70 couples were surveyed as to their on-board bills for a seven-day cruise from Los Angeles to the Mexican Riviera. Following is a summary of the bills for each group.

• Fill in the relative frequency for each group.
• Construct a histogram for the singles group. Scale the x -axis by $50 widths. Use relative frequency on the y -axis.
• Construct a histogram for the couples group. Scale the x -axis by $50 widths. Use relative frequency on the y -axis.
• List two similarities between the graphs.
• List two differences between the graphs.
• Overall, are the graphs more similar or different?
• Construct a new graph for the couples by hand. Since each couple is paying for two individuals, instead of scaling the x -axis by $50, scale it by $100. Use relative frequency on the y -axis.
• How did scaling the couples graph differently change the way you compared it to the singles graph?
• Based on the graphs, do you think that individuals spend the same amount, more or less, as singles as they do person by person as a couple? Explain why in one or two complete sentences.
• See the tables above

• Both graphs have a single peak.
• Both graphs use class intervals with width equal to $50.
• The couples graph has a class interval with no values.
• It takes almost twice as many class intervals to display the data for couples.
• Answers may vary. Possible answers include: The graphs are more similar than different because the overall patterns for the graphs are the same.
• Check student's solution.
• Both graphs display 6 class intervals.
• Both graphs show the same general pattern.
• Answers may vary. Possible answers include: Although the width of the class intervals for couples is double that of the class intervals for singles, the graphs are more similar than they are different.
• Answers may vary. Possible answers include: You are able to compare the graphs interval by interval. It is easier to compare the overall patterns with the new scale on the Couples graph. Because a couple represents two individuals, the new scale leads to a more accurate comparison.
• Answers may vary. Possible answers include: Based on the histograms, it seems that spending does not vary much from singles to individuals who are part of a couple. The overall patterns are the same. The range of spending for couples is approximately double the range for individuals.

Twenty-five randomly selected students were asked the number of movies they watched the previous week. The results are as follows.

• Construct a histogram of the data.
• Complete the columns of the chart.

Use the following information to answer the next two exercises: Suppose one hundred eleven people who shopped in a special t-shirt store were asked the number of t-shirts they own costing more than $19 each.

The percentage of people who own at most three t-shirts costing more than $19 each is approximately:

• Cannot be determined

If the data were collected by asking the first 111 people who entered the store, then the type of sampling is:

• simple random
• convenience

Following are the 2010 obesity rates by U.S. states and Washington, DC.

Construct a bar graph of obesity rates of your state and the four states closest to your state. Hint: Label the \(x\)-axis with the states.

Answers will vary.

Exercise 2.3.6

Sixty-five randomly selected car salespersons were asked the number of cars they generally sell in one week. Fourteen people answered that they generally sell three cars; nineteen generally sell four cars; twelve generally sell five cars; nine generally sell six cars; eleven generally sell seven cars. Complete the table.

Exercise 2.3.7

What does the frequency column in the Table above sum to? Why?

Exercise 2.3.8

What does the relative frequency column in in the Table above  sum to? Why?

Exercise 2.3.9

What is the difference between relative frequency and frequency for each data value in in the Table above ?

The relative frequency shows the proportion of data points that have each value. The frequency tells the number of data points that have each value.

Exercise 2.3.10

What is the difference between cumulative relative frequency and relative frequency for each data value?

Exercise 2.3.11

To construct the histogram for the data in in the Table above , determine appropriate minimum and maximum x and y values and the scaling. Sketch the histogram. Label the horizontal and vertical axes with words. Include numerical scaling.

Answers will vary. One possible histogram is shown:

Exercise 2.3.12

Construct a frequency polygon for the following:

Exercise 2.3.13

Construct a frequency polygon from the frequency distribution for the 50 highest ranked countries for depth of hunger.

Find the midpoint for each class. These will be graphed on the x -axis. The frequency values will be graphed on the y -axis values.

Exercise 2.3.14

Use the two frequency tables to compare the life expectancy of men and women from 20 randomly selected countries. Include an overlayed frequency polygon and discuss the shapes of the distributions, the center, the spread, and any outliers. What can we conclude about the life expectancy of women compared to men?

Exercise 2.3.15

Construct a times series graph for (a) the number of male births, (b) the number of female births, and (c) the total number of births.

Exercise 2.3.16

The following data sets list full time police per 100,000 citizens along with homicides per 100,000 citizens for the city of Detroit, Michigan during the period from 1961 to 1973.

• Construct a double time series graph using a common x -axis for both sets of data.
• Which variable increased the fastest? Explain.
• Did Detroit’s increase in police officers have an impact on the murder rate? Explain.

2.4: Measures of the Location of the Data

The median age for U.S. blacks currently is 30.9 years; for U.S. whites it is 42.3 years.

• Based upon this information, give two reasons why the black median age could be lower than the white median age.
• Does the lower median age for blacks necessarily mean that blacks die younger than whites? Why or why not?
• How might it be possible for blacks and whites to die at approximately the same age, but for the median age for whites to be higher?

Six hundred adult Americans were asked by telephone poll, "What do you think constitutes a middle-class income?" The results are in the Table below. Also, include left endpoint, but not the right endpoint.

• What percentage of the survey answered "not sure"?
• What percentage think that middle-class is from $25,000 to $50,000?
• Should all bars have the same width, based on the data? Why or why not?
• How should the <20,000 and the 100,000+ intervals be handled? Why?
• Find the 40 th and 80 th percentiles
• Construct a bar graph of the data
• \(1 - (0.02 + 0.09 + 0.19 + 0.26 + 0.18 + 0.17 + 0.02 + 0.01) = 0.06\)
• \(0.19 + 0.26 + 0.18 = 0.63\)
• Check student’s solution.

80 th percentile will fall between 50,000 and 75,000

Given the following box plot:

• which quarter has the smallest spread of data? What is that spread?
• which quarter has the largest spread of data? What is that spread?
• find the interquartile range ( IQR ).
• are there more data in the interval 5–10 or in the interval 10–13? How do you know this?
• 10–12
• 12–13
• need more information

The following box plot shows the U.S. population for 1990, the latest available year.

• Are there fewer or more children (age 17 and under) than senior citizens (age 65 and over)? How do you know?
• 12.6% are age 65 and over. Approximately what percentage of the population are working age adults (above age 17 to age 65)?
• more children; the left whisker shows that 25% of the population are children 17 and younger. The right whisker shows that 25% of the population are adults 50 and older, so adults 65 and over represent less than 25%.

2.5: Box Plots

In a survey of 20-year-olds in China, Germany, and the United States, people were asked the number of foreign countries they had visited in their lifetime. The following box plots display the results.

• In complete sentences, describe what the shape of each box plot implies about the distribution of the data collected.
• Have more Americans or more Germans surveyed been to over eight foreign countries?
• Compare the three box plots. What do they imply about the foreign travel of 20-year-old residents of the three countries when compared to each other?

Given the following box plot, answer the questions.

• Think of an example (in words) where the data might fit into the above box plot. In 2–5 sentences, write down the example.
• What does it mean to have the first and second quartiles so close together, while the second to third quartiles are far apart?
• Answers will vary. Possible answer: State University conducted a survey to see how involved its students are in community service. The box plot shows the number of community service hours logged by participants over the past year.
• Because the first and second quartiles are close, the data in this quarter is very similar. There is not much variation in the values. The data in the third quarter is much more variable, or spread out. This is clear because the second quartile is so far away from the third quartile.

Given the following box plots, answer the questions.

• Data 1 has more data values above two than Data 2 has above two.
• The data sets cannot have the same mode.
• For Data 1 , there are more data values below four than there are above four.
• For which group, Data 1 or Data 2, is the value of “7” more likely to be an outlier? Explain why in complete sentences.

A survey was conducted of 130 purchasers of new BMW 3 series cars, 130 purchasers of new BMW 5 series cars, and 130 purchasers of new BMW 7 series cars. In it, people were asked the age they were when they purchased their car. The following box plots display the results.

• In complete sentences, describe what the shape of each box plot implies about the distribution of the data collected for that car series.
• Which group is most likely to have an outlier? Explain how you determined that.
• Compare the three box plots. What do they imply about the age of purchasing a BMW from the series when compared to each other?
• Look at the BMW 5 series. Which quarter has the smallest spread of data? What is the spread?
• Look at the BMW 5 series. Which quarter has the largest spread of data? What is the spread?
• Look at the BMW 5 series. Estimate the interquartile range (IQR).
• Look at the BMW 5 series. Are there more data in the interval 31 to 38 or in the interval 45 to 55? How do you know this?
• 31–35
• 38–41
• 41–64
• Each box plot is spread out more in the greater values. Each plot is skewed to the right, so the ages of the top 50% of buyers are more variable than the ages of the lower 50%.
• The BMW 3 series is most likely to have an outlier. It has the longest whisker.
• Comparing the median ages, younger people tend to buy the BMW 3 series, while older people tend to buy the BMW 7 series. However, this is not a rule, because there is so much variability in each data set.
• The second quarter has the smallest spread. There seems to be only a three-year difference between the first quartile and the median.
• The third quarter has the largest spread. There seems to be approximately a 14-year difference between the median and the third quartile.
• IQR ~ 17 years
• There is not enough information to tell. Each interval lies within a quarter, so we cannot tell exactly where the data in that quarter is concentrated.
• The interval from 31 to 35 years has the fewest data values. Twenty-five percent of the values fall in the interval 38 to 41, and 25% fall between 41 and 64. Since 25% of values fall between 31 and 38, we know that fewer than 25% fall between 31 and 35.

Twenty-five randomly selected students were asked the number of movies they watched the previous week. The results are as follows:

Construct a box plot of the data.

2.6: Measures of the Center of the Data

The most obese countries in the world have obesity rates that range from 11.4% to 74.6%. This data is summarized in the following table.

• What is the best estimate of the average obesity percentage for these countries?
• The United States has an average obesity rate of 33.9%. Is this rate above average or below?
• How does the United States compare to other countries?

The table below gives the percent of children under five considered to be underweight. What is the best estimate for the mean percentage of underweight children?

The mean percentage, \(\bar{x} = \frac{1328.65}{50} = 26.75\)

2.7: Skewness and the Mean, Median, and Mode

The median age of the U.S. population in 1980 was 30.0 years. In 1991, the median age was 33.1 years.

• What does it mean for the median age to rise?
• Give two reasons why the median age could rise.
• For the median age to rise, is the actual number of children less in 1991 than it was in 1980? Why or why not?

2.8: Measures of the Spread of the Data

Use the following information to answer the next nine exercises: The population parameters below describe the full-time equivalent number of students (FTES) each year at Lake Tahoe Community College from 1976–1977 through 2004–2005.

• \(\mu = 1000\) FTES
• median = 1,014 FTES
• \(\sigma = 474\) FTES
• first quartile = 528.5 FTES
• third quartile = 1,447.5 FTES
• \(n = 29\) years

A sample of 11 years is taken. About how many are expected to have a FTES of 1014 or above? Explain how you determined your answer.

The median value is the middle value in the ordered list of data values. The median value of a set of 11 will be the 6th number in order. Six years will have totals at or below the median.

75% of all years have an FTES:

• at or below: _____
• at or above: _____

The population standard deviation = _____

What percent of the FTES were from 528.5 to 1447.5? How do you know?

What is the IQR ? What does the IQR represent?

How many standard deviations away from the mean is the median?

Additional Information: The population FTES for 2005–2006 through 2010–2011 was given in an updated report. The data are reported here.

Calculate the mean, median, standard deviation, the first quartile, the third quartile and the IQR . Round to one decimal place.

• mean = 1,809.3
• median = 1,812.5
• standard deviation = 151.2
• first quartile = 1,690
• third quartile = 1,935

Construct a box plot for the FTES for 2005–2006 through 2010–2011 and a box plot for the FTES for 1976–1977 through 2004–2005.

Compare the IQR for the FTES for 1976–77 through 2004–2005 with the IQR for the FTES for 2005-2006 through 2010–2011. Why do you suppose the IQR s are so different?

Hint: Think about the number of years covered by each time period and what happened to higher education during those periods.

Three students were applying to the same graduate school. They came from schools with different grading systems. Which student had the best GPA when compared to other students at his school? Explain how you determined your answer.

A music school has budgeted to purchase three musical instruments. They plan to purchase a piano costing $3,000, a guitar costing $550, and a drum set costing $600. The mean cost for a piano is $4,000 with a standard deviation of $2,500. The mean cost for a guitar is $500 with a standard deviation of $200. The mean cost for drums is $700 with a standard deviation of $100. Which cost is the lowest, when compared to other instruments of the same type? Which cost is the highest when compared to other instruments of the same type. Justify your answer.

For pianos, the cost of the piano is 0.4 standard deviations BELOW the mean. For guitars, the cost of the guitar is 0.25 standard deviations ABOVE the mean. For drums, the cost of the drum set is 1.0 standard deviations BELOW the mean. Of the three, the drums cost the lowest in comparison to the cost of other instruments of the same type. The guitar costs the most in comparison to the cost of other instruments of the same type.

An elementary school class ran one mile with a mean of 11 minutes and a standard deviation of three minutes. Rachel, a student in the class, ran one mile in eight minutes. A junior high school class ran one mile with a mean of nine minutes and a standard deviation of two minutes. Kenji, a student in the class, ran 1 mile in 8.5 minutes. A high school class ran one mile with a mean of seven minutes and a standard deviation of four minutes. Nedda, a student in the class, ran one mile in eight minutes.

• Why is Kenji considered a better runner than Nedda, even though Nedda ran faster than he?
• Who is the fastest runner with respect to his or her class? Explain why.

The most obese countries in the world have obesity rates that range from 11.4% to 74.6%. This data is summarized in the table belo2

What is the best estimate of the average obesity percentage for these countries? What is the standard deviation for the listed obesity rates? The United States has an average obesity rate of 33.9%. Is this rate above average or below? How “unusual” is the United States’ obesity rate compared to the average rate? Explain.

• \(\bar{x} = 23.32\)
• Using the TI 83/84, we obtain a standard deviation of: \(s_{x} = 12.95\).
• The obesity rate of the United States is 10.58% higher than the average obesity rate.
• Since the standard deviation is 12.95, we see that \(23.32 + 12.95 = 36.27\) is the obesity percentage that is one standard deviation from the mean. The United States obesity rate is slightly less than one standard deviation from the mean. Therefore, we can assume that the United States, while 34% obese, does not have an unusually high percentage of obese people.

The Table below gives the percent of children under five considered to be underweight.

What is the best estimate for the mean percentage of underweight children? What is the standard deviation? Which interval(s) could be considered unusual? Explain.

Blog – Creative Presentations Ideas

infoDiagram visual slide examples, PowerPoint diagrams & icons , PPT tricks & guides

How to Present Time Management Matrix Visually for Easy Understanding

Are you presenting time management topics? Consider using a visual way of explaining decision-making and time management methods, such as the Eisenhower matrix. 

We show an idea on how to present the four quadrant boxes of decision-making and planning of action priorities.

The graphics presented here are based on our diagram design experience for presentations that focus on clarity and information visualization. 

Get all the graphics presented here – click on the slide pictures to see and download the source illustration. Check the full Eisenhower Matrix for Time Management Presentation (PPT Template).

What is a time management matrix?

Also called Eisenhower Matrix is a simple tool for prioritizing actions. Organizing task in the matrix layout helps to decide on task priority and focus on what’s critical. 

The idea is to group actions into four boxes, organized by two categories: urgency and importance, as you can see below. 

It helps you to decide what task to do first, what to schedule for later, what to delegate, and what to eliminate. This time management framework suggests you to classify your asks as: 

• Urgent & Important (tasks that require immediate attention and have a significant impact), 
• Important & Not Urgent (important but not time-sensitive task), 
• Urgent & Not Important (time-sensitive but not crucial issues, 
• Not Urgent & Not Important (neither pressing nor critical).

If you want to present this management approach visually, create a visual representation that is simple and clear. We created such a slide with this in mind.  

The slide with the Eisenhower Matrix consists of four parts. We used non-standard shapes to make the visual effect more interesting. Each box refers to one prioritizing action. Each of them is highlighted with a distinctive color. Therefore, green is used to signify tasks to be done and red signifies tasks to be deleted. Thanks to this distinction, you can easily show actions by category. Additionally to each box, we added icons that symbolize categories. 

Such a composed slide helps users focus on what matters most, ensuring a quicker way to explain the idea of this time management framework. 

Presenting benefits of using Eisenhower matrix based decision making

If you want to list the benefits of this time management method, do it in some interesting visual way instead of having only list of bullet points. For example, you can use diagrams with icons illustrating each benefit. It is easy for your audience to grasp the advantages at a glance.

In the slide above, we show you the idea of a slide about decision-making advantages. Here we had four benefits, but this design is easy to change for more and fewer points. 

We used round shapes. The shape of a circle is softer and signifies continuation and flow. If you want to evoke a positive association,  consider using round shapes in design. Of course, these associations can vary based on personal experiences, but it’s some common principle. In this case, we combined a few different shapes to create visual interest. Remember that simplicity is key in design, so avoid using too many shapes, just try to convey a complex message in a simple way.

Share examples – Time Management from Financial sector

Here’s an example of how such a matrix can look filled with specific tasks from the fintech industry. 

Example tasks can include each section:

• Responding to a critical tax audit – this would be Do First
• Negotiating with a key lender to restructure debt – this would be Do First
• Developing a long-term financial forecast – this would be Scheduled
• Analyzing costs and benefits of new software –  this would be Scheduled
• Regularly browsing personal social media at work – this would be Deleted
• Responding to every single email notification – this would be Deleted
• Preparing travel arrangements for an upcoming conference – this would be Delegated
• Generating routine financial reports – this would be Delegated

From the design point of view, notice how we used small details to make the slide consistent … bullet-point coloring corresponds to meaning – red for delete, yellow for delegate, blue for schedule, and finally green to do.

One of the important roles of a slide is creating impactful and effective designs that not only look beautiful but also communicate the right message to her target audience. In this example, we focus on the design flow between tasks and each section so that it can be easily read. 

It’s an example of the financial industry, so we also used the financial icon in the middle of the slide to illustrate the subject.  

Example of Net Zero Actions Priorities for a municipality

Here’s another example of prioritizing actions of Net Zero activities that a city can do. Following Eisenhower matrix, those  tasks can be assigned to 4 groups. 

Example of global warming mitigation tasks can include

• Emission assessment – this would be Do First
• Energy Efficiency Upgrades – this would be Do First
• Fossil Fuel Phase – this would be Scheduled
• Emissions Reduction Milestones  – this would be Scheduled
• Supplier Engagement – this would be Delegated
• Research Partnerships – this would be Delegated
• Ignore Stakeholder Engagement – this would be Deleted
• Delay Emission Reductions – this would be Deleted

You can present it as a to-do list graphics on a slide, as we did below. 

To visualize these tasks we created 4 fields, each for one section. As in the previously discussed slide of Eisenhower Matrix in this slide we used the same idea about distinctive color and icons for each section. For better recognition subject we added also the icon of the cloud with 0% that refers to reaching net zero.

If you would like the slide design to be more interesting, you can experiment with background. We suggest adding some picture with the mask layer. The slide looks more balanced and sophisticated.

Example of IT Tasks ToDo matrix 

Another example is for IT department or IT related tasks organization. This can include

• Server outage fix – this would be Do First
• Critical Security Breach – this would be Do First
• Strategic Planning – this would be Scheduled
• Travel Arrangements – this would be Delegated
• Routine Report Review – this would be Delegated
• Social Media Monitoring – this could go to Don’t do group

This tasks management slide design focuses on the visual way of representing To-do list. Each task is placed in a separate field with various colors. You can add visual markers to indicate the status, of what is done and what is not done. It’s an easy way to make a harmonized slide with a to-do list. 

Illustrating time management presentation by a quote

To make your your presentation more engaging, you can present a time management quote. To do so  you can consider using our slide design idea we show below. 

We suggest inputting the quote in a speech bubble, it’s a common way to draw the eye to important elements in your design.  Moreover, you can add icons with quotation marks thanks to which the audience will know that the slide is about citation. We also added a picture on the background to illustrate time management. 

Key Tips How to Present …

When you create a presentation of your Time Management presentation, keep these simple design guidelines in mind for a clear, captivating, and easily understandable delivery:

• use a consistent graphical style throughout your presentation to maintain visual coherence,
• plan the layout of your slides, particularly for those containing a lot of text or data, to ensure a well-balanced and engaging design,
• add icons to enhance the visual appeal of your presentation,
• consider using distintive shapes and colors to highlight the content,
• convey your message with a simple and balanced design, for visual interest, you can add a picture with a mask layer on the background. 

By following these basic design principles, you can create a compelling presentation that leaves a lasting impact on your audience.

Resource: Eisenhower Matrix for Time Management Presentation PowerPoint Template

The examples above used the graphics from an Eisenhower Matrix for Time Management Presentation (PPT Template).  All slides are available in the infoDiagram collection of presentation graphics.

Moreover, you can extend your data presentation with an Eisenhower Matrix for Time Management Presentation (PPT Template) right here.

10 Free Canva Alternatives For Eye-Catching Designs And Presentations

I n the digital age, eye-catching designs and stunning presentations are more important than ever. Canva has long been a go-to tool for creating these visuals. However, there's a world of options beyond Canva, each with its unique strengths and capabilities.

Whether you're a small business owner, a blogger, or someone looking to spruce up a presentation, each of these tools has something helpful to offer. They made the list not just for their affordability but also for their ease of use and flexibility in design. From editing PDFs to creating social media graphics and beyond, these platforms can expand your creative possibilities.

We have explored each alternative's features, such as background removal tools, advanced editing capabilities, and user-friendly templates. The goal is to equip you with the knowledge to choose the right tool for your design needs so you can create stunning visuals without breaking the bank. Here are the best 10 free Canva alternatives for eye-catching designs and presentations.

Read more: Major PC Brands Ranked Worst To Best

Stencil  is a great tool for creating easily shareable images tailored for social media, small business owners, and bloggers. Stencil's focus is to make image creation easy with a free all-in-one app. It has an impressive stock photo library available to both free and premium users, and creating images for social media or blog posts is intuitive. The actions are simple clicks and drag-and-drop functions that users of all tech and graphic design levels will recognize.

Posting images is simplified through several convenient features. Users can directly send images via SMS or post them to Facebook or Instagram feeds through login integration. Additionally, there's an option to connect with a Buffer account to schedule posts after creation. Stencil's free option allows users to save 10 images per month with access to a limited stock library. It won't be enough for a full-time blogger, but it's a great test drive. Unlocking everything Stencil has to offer costs $12 per month or a yearly fee of $86.40. This essentially removes all limitations and gives full access to its stock library. There are no other microtransactions or add-ons.

Snappa is another great alternative to Canva, especially if you're not a graphic designer. Its user interface is remarkably user-friendly, with easy adjustments made through simple sliders and menus. Snappa has over 6,000 templates to get started with, as well as an impressive library of free images and graphics. The images provided are royalty-free and can be used for any project without incurring additional costs.

The downside to Snappa's simplicity and ease of use is that graphic designers may find it lacks the functionality of some of the other services on this list. It's ideal for beginners and those who need an image but don't have any idea how to make one.

Snappa's free version functions more like a trial, granting access to all templates and images but limiting users to only three downloads per month. Access to all other features requires a paid account, which is priced at $15 per month or $120 annually -- equivalent to $10 per month.

Adobe Express

While the AI image creator Adobe Firefly has been getting most of the press these days, Adobe still has plenty of traditional image editing tools available. One of the most affordable is  Adobe Express , an entry-level software that's ideal for those unfamiliar with Adobe's range of products and as a user-friendly image creation and editing tool.

You'll find many of the standard Adobe tools you would with Photoshop and other Adobe products , but they have been streamlined for ease of use for beginners. Users can quickly create images for social media and smaller projects with ease. Included are numerous templates that can be customized for different projects, as well as options for creating vector images.

The free version of Adobe Express provides users with a limited capacity for image generation each month and offers access to a basic range of templates and stock photos. For those who want more comprehensive features, there's a premium subscription available at $100 per year or $10 per month that unlocks full access to all tools and an extensive stock library.

Adobe Express is much more intuitive and easy to use than Photoshop, making it a good starting point for beginners. However, those without any design experience may find it a bit challenging. In addition, more experienced users will find it easy to use but less comprehensive than Photoshop.

If you're looking for a powerful no-frills editor, Pixlr X is a great place to start. It's completely free, although the website monetizes itself through ads. However, this means you don't even have to make an account and can jump right into editing and content creation.

As a free product, Pixlr X offers its complete range of features through a web app. The app itself has a streamlined interface with menus that provide a wide array of customization tools and options, allowing precise image alterations according to user preferences.

The software includes templates and settings for virtually every need. It features ready-made templates for popular social media platforms like Facebook, Instagram, and Twitch, allowing users to create perfectly sized images right from the start. Additionally, Pixlr offers templates for podcast cover art and much more.

The user interface of Pixlr X is clean and uncluttered, without any distracting graphics. It presents a simple menu packed with various editing options. The toolset is comprehensive, making it easy for beginners to use while also offering enough advanced features to satisfy experienced users and graphic designers.

VistaCreate

VistaCreate is an excellent tool for creating visual marketing materials and ads for your business. The platform is designed to be easy to use and user-friendly while still providing visually impressive results. It offers templates for different seasons and industries that users can easily alter and customize to quickly create promotional materials, even if they lack an eye for design. Included with the editor is a massive library of tools like stock photos, videos, logos, fonts, and more that all can be used for free without licensing issues.

Signing up for the premium membership unlocks all of the available templates and graphics. Most users won't be stunted by the offerings from the free version, but the premium version has significantly more variety. If you want to try it before you buy, VistaCreate does offer a 14-day trial that gives access to the premium version. However, this trial requires a credit card entry, so you need to remember to cancel before the trial period ends to avoid charges.

The free version is free forever. It offers a respectable 10 GB of storage for projects and files. The premium version has unlimited storage, more templates and graphics, and access to unique tools like a background remover and instant sticker makers. VistaCreate premium costs $13 per month or $10 per month if paid annually.

Visme is a fantastic and incredibly versatile tool. It's a single app that can do most things that you'd want from an image editor, plus a few extra features that go beyond simple image content creation and editing. 

Like many other platforms, it has a host of templates, fonts, and stock images that make it easy to create brandable materials, social media posts, and digital media. However, in addition to the simple image editor, Visme also has a lot of intuitive tools for small businesses. Users can easily upload data from spreadsheets and graph it visually using a simple, drag-and-drop interface that can readily be branded. Images and content you create on Visme can also be turned into videos and edited directly on the platform.

The only downside to Visme is its price. The website offers a free version that allows you to take the system for a test drive, but it doesn't allow you to export any of the files that you create. While there may be workarounds, it may be better to consider purchasing a membership or choosing another service from this list. The Starter membership costs $12.25 per month when paid annually, or $29 monthly, and the Pro membership costs $24.75 per month when paid annually, or $59 billed monthly. Although this pricing is on the higher end compared to other services, Visme's comprehensive all-in-one solution justifies the cost for many users.

If you need infographics, PowerPoint presentations, or short videos, then Piktochart is one of the best alternatives to Canva. The platform doesn't concentrate on pure image design and generation. Instead, it focuses on bringing data to life through fun and interesting infographics.

For businesses that generate significant traffic through social media or understand the value of SEO, Piktochart recognizes that a well-crafted infographic can be a powerful asset. Its tools and templates are designed to present data in a visually attractive manner, highlighting key points. All of Piktochart's tools and templates present data in visually appealing ways while still clearly showing key data points. The user interface is very user-friendly and comes with tutorials on every aspect of the system. There's even a quick crash course that claims can get you up and running within an hour.

Piktochart also has rudimentary video editors that are surprisingly easy to edit. While it may not offer the extensive functionality of dedicated video editing software, it meets the needs of most users. There's also the option to quickly turn images into PowerPoint presentations and videos, making it an excellent choice for office workers. Piktochart is free but only offers limited online storage options. It's essentially a forever-free trial that allows users to get started with the system and determine if they can make use of it. The paid version costs $14 per month when paying annually or $29 monthly. 

The makers of DesignCap took all the fun aspects of making a poster or collage for grade school and turned it into software. Surprisingly, the software is known for its ease of use, making image creation as straightforward as those school projects.

DesignCap presents itself as a one-stop shop for all of your design needs, but in reality, it works better if you look at it like a poster maker. The platform can help users create simple images using templates and tools for social media posts, cards, wedding invitations, posters, and social media.

While it's not advanced enough for a professional graphic designer, it is ideal for someone who needs to make some eye-catching visuals. The free version has a smaller library of templates and stock photos available and is limited to five image saves. The only other limitation is export file formats. It has fewer options than some of the others on this list, but if you just need JPEGs to post or create images quickly, DesignCap is a great resource.

For more advanced users on a budget, Photopea is a fantastic solution. Photopea is not specifically tailored for bloggers or social media users -- instead, it is fundamentally an image editor. This focus on image editing first is reflected in its user interface and color scheme, which might not be specifically designed for bloggers and influencers but still offers useful functionality for them. The UI is very bare bones, devoid of any testimonials or marketing trying to upsell users.

Upon visiting the Photopea site, users can immediately upload and start editing images. The more you use Photopea, the more functionality you'll discover in the software. Users can create vector images, create layers, apply filters, and so much more. There's a dedicated tutorial section of the site to help users navigate the numerous features. If you can't find the answer there, Photopea also has a very active Reddit community as well as email support.

Photopea is unique in that beginners can do all of the simple editing that they'll need, while advanced graphic designers will also find a lot of useful tools to make something truly memorable. Photopea is a free service that supports itself through ads. Users have the option to purchase a premium membership, which removes ads and supports the developers. The free version already provides full access to all features, although premium users benefit from prioritized email support.

Desygner is a budget-friendly alternative to Canva that was specifically designed to be a more user-friendly alternative to Adobe InDesign. Desygner has intuitive controls that allow users to easily choose and modify templates. Like many of the other alternatives on this list, it comes equipped with a large stock image and template library that is free to use for commercial and personal use.

One of its best features is its PDF editor. All of the easy-to-use tools can be used to edit and alter PDFs to create impressive documents. These are perfect for flyers, notices, resumes, and much more. This task can often be tricky in standard word processors, but Desygner simplifies it with the same tools used for image creation. Another standout feature of Desygner is its background removal tool. If you've been creating images for a business, you'll know how essential this feature is, not to mention how frustrating it can be when it doesn't work well.

In terms of affordability, Desygner is very budget-friendly. Its pricing is among the most economical on this list, at approximately $5 per month when paid annually or $10 paid monthly. The free version of Desygner provides access to many of its tools and templates. While the free version is sufficient for smaller businesses and casual users, the premium version is a worthwhile investment for regular image creators. It includes the background remover tool and offers a significantly larger selection of stock images and templates.

Read the original article on SlashGear .

Games With The Most Impressive Graphics

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Forza Horizon 5: The 9 Best Cars For Skill Points

7 new things final fantasy 7 rebirth teaches us about the lore, the best 2d super mario games, ranked.

As video games have continued to grow and evolve as both entertainment and art, the games just keep looking better and better. If someone is playing on a high-end PC or the average console, it's hard not to notice when a game stands out a bit more than the rest.

10 Games With The Best Graphics Ever (At Their Time Of Release)

Gorgeous graphics tend to make an average game ten times better, and these games in particular wowed players with incredible visuals.

Whether it is the highest fidelity graphics or just a gorgeous art style (or both), games that look good usually also play well. If that much time gets spent in the graphics department they must have something good elsewhere. Here are the games with the best graphics out there.

Updated on May 12, 2024 by Mark Sammut: Two recently-released games deserve to be spotlighted. One is the latest entry in a long-running JRPG franchise, while the other is a new IP from a Korean studio.

A few criteria/things to keep in mind:

• This article focuses on modern releases and a few post-2000s projects rather than classics from the NES, SNES, Game Boy, Genesis, and PS1 eras. As important and industry-pushing as the latter were, visually they are too different from modern releases to compare them.
• The games are only loosely ranked since graphical styles vary so much from project to project, and personal preference plays a part.
• A 2016 game might be ranked higher than a 2024 one because the former was more impressive when it debuted, even if the latter technically looks better.

Lords Of The Fallen

Unreal engine 5 is here, lords of the fallen (2023).

Epic's Unreal Engine 5 was introduced in 2020, instantly garnering hype for what it could mean for the industry's future. In 2023, a few notable games that utilize the engine were finally released, presenting early examples of its potential. Remnant 2 and Immortals of Aveum are both visually impressive, and the same could be said for ARK: Survival Ascended.

Lords Of The Fallen: Hardest Bosses, Ranked

The are over 30 different bosses to find and overcome in Lords of the Fallen, and some of them are a lot more difficult than their peers are.

However, at the moment, Lords of the Fallen is probably the most gorgeous UE5 game , although that could change once titles like Senua's Saga: Hellblade 2 are released. While not without its issues, the Soulslike game's graphics are certainly not among them. Axiom is a vast and stunning hellscape, one that has quite a bit of variety. The game's lighting and animations are consistently top-notch too.

Bright Memory: Infinite

A one-person team.

Games and their visuals cannot be analyzed in a vacuum. Context and expectations shape somebody's reaction to an experience, and that is certainly the case with Bright Memory: Infinite . Developed by a single developer, Zeng Xiancheng, this first-person shooter originally debuted in 2020 as Bright Memory , a concept that was expanded for a full release in July 2022. While the overall game has plenty of issues, its graphics are undeniably impressive, comparing favorably with higher-budget titles.

There are plenty of gorgeous indie titles, but the vast majority succeed because they do not try to emulate AAA projects. They strive to do their own thing. Bright Memory: Infinite does the exact opposite, and the game proves that it can be done well.

Burst Of Color

Announced and released out of nowhere, Hi-Fi Rush was perhaps 2023's greatest surprise . Tango Gameworks' action game blends hack and slash combat with rhythm-based mechanics, rewarding players for adhering to the beat. Set in a corporate city run by Vandelay Technologies, the title brings to life a vibrant and bustling metropolis filled with unique buildings and NPCs.

As the campaign is linear, Hi-Fi Rush focuses on creating cool environments and backdrops, two things the game absolutely nails. Quite a few stages are predominantly set within samey corridors and indoor areas, but whenever the action heads outside, Hi-Fi Rush really comes alive.

An Animated Painting

There aren't many games that have been able to graphically stand the test of time as well as Okami has. Originally released in 2006 on consoles like the PlayStation 2 and Wii, Okami was able to take advantage of its timeless style to make the most out of the hardware it was on.

However, playing Okami on those consoles today shows just how much the original systems were holding it back, which is where the HD version comes in. On the PS4 and Switch, Okami 's classical Japanese art style looks absolutely stunning in just about every area of the game.

Heavenly Sword

Motion capture showcase.

Most of Ninja Theory's bigger games boast stellar visuals and character designs, however, Heavenly Sword gets the nod because it was the studio's first proper graphical showcase. More impressively, the early PS3 game still looks beautiful today, an achievement that should be largely credited to the project's use of motion capture technology.

The cut-scenes steal the show and could easily pass for a mid-budget animated flick, with Andy Serkis' performance as King Bohan ranking among the best in any era of gaming. During gameplay, Heavenly Sword is also a treat for the eyes and senses, particularly in its lavish environments.

Killzone: Mercenary

Console quality on a handheld system.

Regardless of their quality, all the Killzone games are graphical showcases. Despite being a launch title, 2013's Shadow Fall is still among the most visually impressive games on the PS4. As stunning as Guerrilla's mainline entries are, Killzone: Mercenary deserves a special mention due to its hardware.

The PS Vita was and still is a reasonably powerful handheld device, one that could replicate home console visuals to a certain extent. No other title highlighted the console's graphical potential better than Killzone: Mercenary , an FPS that would not have looked out of place on the PS3 or even as a budget PS4 project. The fact it is also a decent game does not hurt either.

Super Mario Odyssey

It is not always about realism or processing power.

While combining "Nintendo Switch game" with " best graphics " might seem weird, it's hard to argue that Super Mario Odyssey doesn't make the most of the console's limited processing power. With a combination of stylized art and impressive HD, Mario explores several gorgeous landscapes that might inspire players to sit back and think about how far things have come.

Nintendo has always used fantastical art styles to produce charming and timeless games that don't break the bank on processing. Mario has never looked this good , and sequences like the New Donk City music festival allow the game to shine.

Suicide Squad: Kill The Justice League

For all its faults, the graphics are not one of them.

All of Rocksteady's games push the envelope in terms of visuals, and 2015's Arkham Knight still boasts the most impressive rendition of Gotham in gaming. Its visuals have aged magnificently, and the gameplay is fantastic, even if the overall project is not quite on the same level as Arkham Asylum or Arkham City . After an 8-year wait, Rocksteady made its comeback with Suicide Squad: Kill the Justice League ; unfortunately, the Arkhamverse spin-off garnered a very mixed reception. Focusing on looter shooter action in an attempt to be a live-service experience, Suicide Squad is a fairly confused project that does not seem to play to Rocksteady's strengths.

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While many elements warrant criticism, and it can be tempting to dismiss the entire project, the game is not without positives. If nothing else, the graphics are generally top-notch, particularly when it comes to the cutscenes and character designs. When the action gets going, the screen can get rather muddled, but it is not devoid of visual flare either. For all its faults, Suicide Squad certainly looks like a proper AAA project.

Halo: Reach

A series that always pushed console graphics to their limits.

In truth, Reach could be regarded as a stand-in for Halo in general as Microsoft's franchise is consistently pushing console visuals to their limits. In terms of art style, Halo 4 certainly has its fans; when it comes to graphical prowess, Halo 5 and Infinite are unsurprisingly a step above their predecessors. However, Halo: Reach perfected the series' iconic aesthetic of Bungie's era, ensuring the latter's time with the license ended on a high note.

Nowadays, Reach looks its best in The Master Chief Collection , which enhances the visuals in a few subtle but notable ways. That said, the Xbox 360 version holds up well after all these years.

Dragon Ball Z: Kakarot

At times, looks (much) better than the anime, dragon ball z kakarot.

It wasn't until fairly recently that video games hit the graphical fidelity necessary to be able to fully translate animated shows and films into live gameplay, with recent Dragon Ball games being the most shining examples. 2018's Dragon Ball FighterZ was able to take a page out of Guilty Gear 's book to make a stunning 2.5D experience, but gorgeous, fully 3D anime games were still a rarity.

Until Dragon Ball Z: Kakarot was released, that is. Taking the Toriyama characters and landscapes that fans know and love, Kakarot turns them into stunning 3D models with some of the most impressive animations and visual effects around.

Lego Star Wars: Skywalker Saga

Detailed & beautiful, lego star wars: the skywalker saga.

Lego projects might not be as graphically intensive as games with realistic visuals, but they have a unique and clean aesthetic that generally complements their gameplay and tone. Although the franchise's IP adaptations are consistently pleasing to the eyes, Lego Star Wars: The Skywalker Saga exists on a whole other level. Covering all the main episodes in the sci-fi film series, the game beautifully recreates some of the most iconic locations in Star Wars , creating worlds that are expansive and detailed.

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Undoubtedly the most ambitious Lego title, The Skywalker Saga is the full package, and Traveller's Tales' hard work is evident throughout the experience. While very much designed with younger players in mind, die-hard fans are likely to have a blast regardless of their age; in fact, people who are just searching for an action-adventure romp should check this release out.

A Gorgeous World To Take On The Go

In terms of raw power, the Game Boy Advance has nothing on the Nintendo DS, let alone something like the Switch; however, that does not mean the classic console's library is devoid of gorgeous games . Golden Sun is a turn-based JRPG set in Weyard, a fantasy world that is refreshingly diverse in terms of environments.

Largely experienced from a top-down perspective, Golden Sun looks like most other old-school JRPGs found on the GBA or SNES, just with its graphics maximized to their full potential. Camelot instilled every town and dungeon with color and personality, while battles come to life with a flurry of effects that are dazzling to behold.

South Park: The Fractured But Whole

Looks exactly like the show.

When adapting an established property to a different medium, concessions usually need to be made. However, exceptions do exist, and South Park: The Fractured but Whole managed to perfectly replicate the show's aesthetic. The RPG looks and sounds exactly like Trey Parker and Matt Stone's legendary animated series, permitting fans to immerse themselves in this world like never before.

Even removed from that context, The Fractured but Whole 's visuals are detailed, expressive, and clean. Authenticity did not come at the cost of quality.

Shadow Of The Colossus (2018)

Majesty in gaming form, shadow of the colossus.

For the most part, this article focuses on modern games rather than titles that were graphical showcases when they debuted. Shadow of the Colossus both follows this rule and is also an exception; while the PS2 version looks dated, the visuals still retain that same sense of wonder and scale that they had when the game originally came out in 2005.

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Bluepoint Games' 2018 remake gives Team Ico's classic a modern makeover, and traversing the Forbidden Land in search of majestic colossi remains as haunting of an experience as it was in the PS2 era.

Stellar Blade

More than just eve.

In the lead-up to its release, Stellar Blade 's marketing heavily advertised Eve, its AI protagonist, and her wardrobe. Attractive characters being used to sell projects is nothing new, but their heavy promotion usually suggests a lack of trust in the rest of the game's quality.

Surprisingly, Stellar Blade proved to be way more than just its main character. Shift Up created an exciting action game with Soulslike combat (along with hack and slash influence) that also features surprisingly expansive zones that allow for exploration, side quests , and environmental storytelling. Considering it was created by a smallish studio compared to other PS5 first-party titles, Stellar Blade compares favorably to most of Sony's heavyweights, and it is among the best-looking Unreal Engine 4 games of all time. In fact, it could be confused for Unreal Engine 5.

Persona 5 Royal

Oozes style.

As hundreds of games use an anime aesthetic, they start to blend together if they do not inject enough personality into their presentations. Persona 5 Royal does not have this issue. Everything about the game screams "stylish," and that holds true for the social sim and dungeon crawling sections of the campaign. The latter take place in diverse Palaces that are generally vibrant, lively, and gorgeous.

The visuals also do a lot of heavy lifting during battles, elevating what is a rather unspectacular turn-based combat system. Outside of Palaces, P5R unleashes players on a small but dense variant of Tokyo, one brimming with tiny details that enhance the experience.

Persona 3 Reload is quite a looker as well, although its single-dungeon setup restricts variety when compared to Persona 5 Royal 's Palaces.

The Last Of Us 2

Gritty realism & tremendous performances, the last of us part 2.

Naughty Dog's games are always on the cutting edge graphically. 2016's Uncharted 4: A Thief's End has barely aged a day since its release, and 2013's The Last of Us was a contender for the most visually impressive game of the seventh generation. Therefore, unsurprisingly, the studio's latest offering, The Last of Us 2 , is a powerhouse in the graphics department.

This action-adventure game features realistic visuals and grounded performances courtesy of Naughty Dog using performance capture . Whether players are viewing a rare quiet moment or crawling in the mud to avoid a Clicker, The Last of Us 2 looks incredible. The 2024 remaster enhances the base version even further.

Weather Effects & Environments

The newly titled Gears 5 takes a series that has always looked good and elevates it to the next level. The game's campaign takes place across a wide variety of environments, from a jungle early on to a snowy tundra and red desert landscape.

The snowy tundra and red desert are also the locations for the game's more open exploration sections, giving a chance to explore and take in all the scenery. Gears 5 's cutscenes are also gorgeous and the high fidelity extends into all the game's other modes.

Assassin's Creed Odyssey

Packed with stunning vistas, assassin's creed odyssey.

Assassin's Creed Odyssey earns its subtitle over the 60-plus hours it takes to mainline the story; in the meantime, players get to appreciate and take in the beauty of Ancient Greece. While the environments don't vary a ton from Assassin's Creed Origins , the extra trees and seas make for some spectacular views.

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With the viewpoints, Odyssey never hesitates to point out just how magnificent it looks. Most of the main characters and side characters also look great, which is impressive based on the quantity.

Personality & Vibrancy

Supergiant Games has put together some of the greatest indie releases of all time, and the studio's crowning achievement is Hades . The roguelike follows Zagreus' repeated attempts to make the journey from the Underworld to Mount Olympus , a task that proves to be anything but simple for Hades' son.

Hades ' visuals are vibrant, thematically consistent, and lively. The game's environments and characters are soaked in mythology and personality, while the particle effects are fantastic and impactful. The only negative is that sometimes there is a bit too much happening on screen.

Hades 2 arguably looks better than its predecessor, but it is still a work in progress at the moment.

Perfectly Mimics Classic Cartoons

A unique and eye-catching art style is often more important than sheer graphical prowess, and Cuphead might be the best demonstration of this point. Inspired by cartoons of old, Studio MDHR created a game that uses stunning and dynamic hand-drawn animation to bring to life a colorful world and the beings that exist within it.

Even though they do not get much in the way of backstory, Cuphead utilizes its presentation to get across the personalities of each boss. The art style is also consistent throughout the campaign, allowing for a coherent experience despite most of the characters boasting designs that share very little in common.

Horizon Forbidden West

Scale & quality.

Guerrilla Games somehow managed to outdo Horizon Zero Dawn with its sequel, despite the latter still coming out on the PS4 alongside the console's successor. Horizon Forbidden West finds Aloy exploring a new area of this setting, one specifically inspired by states and cities like California and San Francisco. The result is a gorgeous and vast world packed with lush natural environments that are home to intricate mechanical beasts.

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Like most open-world games , Horizon Forbidden West does not always look absolutely fantastic, but its high points are so impressive that they make the more forgettable moments forgivable. While still a beautiful game on the PS4, this 2022 release is, unsurprisingly, at its best on the PS5.

Ori And The Will Of The Wisps

Great use of color & light, ori and the will of the wisps.

Moon Studios' Ori games are some of the best modern Metroidvanias, and they knock it out of the park in nearly every area. They tell emotional storylines that succeed in fostering not only a connection between the audience and the silent eponymous character but also the world they live in. Gameplay-wise, both games have precise and challenging platforming, while Will of the Wisps also introduces combat to the mix. Although a touch polarizing, the latter nevertheless adds an extra dimension to the overall package.

Last but not least, Ori and its sequel are both visually enchanting. The games' use of color might be among the best in the entire industry, and each environment is a work of art. In the world of side-scrollers, not many projects compare favorably to Ori and the Will of the Wisps in any department, including graphics.

Demon's Souls (2020)

A beautiful hell, demon's souls.

As mesmerizing as Elden Ring 's visuals can be at times, the game's open-world design means they are spread a bit thin; conversely, 2020's Demon's Souls remake consists of almost nothing but stunning areas. Rife with deadly creatures, haunting architecture, and intimidating landscapes, Boletaria is a gorgeous nightmare of a kingdom that is equally likely to leave players in awe or fear.

As a launch title for the PS5, Demon's Souls served as something of a tech demo for the hardware, showing what the next-gen console could accomplish. This is a game that could not exist on the PS4, and even more than 18 months into the PS5's life, Demon's Souls still has some of the best graphics on the system.

Ghost Of Tsushima

Immersive open-world, ghost of tsushima.

Gazing across Ghost of Tsushima 's rendition of the Japanese archipelago is quite the sight to behold, as this highly anticipated title has some breathtaking scenery. Tsushima 's main graphical focus is on its world, which ends up feeling just as alive as the characters that inhabit it.

The way cherry blossom petals flow in the highly stylized wind, how the sunset illuminates the beautiful countryside, and the many vibrant colors that contrast the violent gameplay make for one beautiful game .

Ratchet & Clank: Rift Apart

Pixar quality, ratchet and clank: rift apart.

Similar to 2016's Ratchet & Clank , Rift Apart 's animation is on a whole other level. The franchise's most recent entries tend to be compared to Pixar's movies, which is about as high of praise as any game can receive. Utilizing the full power of the PS5, Ratchet & Clank: Rift Apart matches top-tier cutscenes with gameplay sections that are packed with detail, moving parts, and depth.

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Insomniac created lavish and dense worlds that all have unique flavors that make them exciting to explore. When the action gets going and Ratchet or Rivet scoop up bolts, Rift Apart is as smooth as butter.

Marvel's Spider-Man 2 is also visually stunning and represents Insomniac at its best. Rift Apart merits the nod due to being among the first PS5 projects to showcase the console's graphical potential, but Spider-Man 2 is as good-looking of an open-world game as they come.

Ni No Kuni: Wrath Of The White Witch

Ghibli quality, ni no kuni: wrath of the white witch.

Except for Square Enix, Level-5 is arguably the most consistent JRPG developer in terms of visuals. Yo-kai Watch , Dragon Quest 8 , and Dark Cloud 2 are all gorgeous, and the latter's art styles are timeless. Level-5's graphical masterpiece is undoubtedly 2013's Ni no Kuni: Wrath of the White Witch , although the developer got some help as the game's cutscenes were handled by Studio Ghibli.

The anime studio is well-known for its lavish cinematic productions, and Wrath of the White Witch replicates Ghibli's iconic style splendidly . Even if the cutscenes were ignored, Ni no Kuni would still rank among the PS3's most beautiful games .

Resident Evil 2 (2019) – Represents All Modern Resident Evil Games

A remake done right, resident evil 2 (2019).

Years of remasters and rereleases have cemented the idea that old games can look better than they did, but not as good as modern ones. Capcom rebuilding Resident Evil 2 from the ground up makes it a modern video game, a fantastic one at that. Leon and Claire have never looked this good and neither have the zombies and monsters terrorizing Raccoon City.

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The police station and underground lab look nearly life-like and every scare in the game is extra terrifying with how detailed the monsters are. Even Tyrant looks awesome, in his own terrifying way.

Resident Evil 3 and Resident Evil 4 also look fantastic, but RE2 received the nod as it was the first of Capcom's stint of recent remakes. Resident Evil Village is also stunning.

Microsoft Flight Simulator (2020)

The world at the player's fingertips, microsoft flight simulator.

Microsoft Flight Simulator is a jaw-dropping achievement. The flight sim grants players access to the world, allowing them to plan and take trips to Earth's highest mountains, hottest deserts, and greatest metropolises. The game's scope is impressive, and this ambition is more than matched by its technical prowess.

Microsoft Flight Simulator is arguably the most realistic game of all time, with both the planes and locations authentically mirroring their real-life counterparts to the smallest detail.

God Of War (2018) & Ragnarok (2022)

A new era, a new look, god of war: ragnarok.

Nothing against the previous installments of God of War , which are all technical showcases in their own right, but the soft reboot of the 2018 sequel and its successor are not only different but also more gorgeous. Exploring the Norse lands to soak up this universe's mythology is spectacular for a number of reasons, including the fact that everything looks great.

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God of War captures Kratos and Atreus in a way that gives depth to the former not experienced in previous installments. Unsurprisingly, God of War: Ragnarok maintains the high quality set by its predecessor. Graphically, the sequel does not offer a huge leap forward, but that is a testament to God of War 's beauty rather than a criticism of Ragnarok ​​​​​.

The Legend Of Zelda: Tears Of The Kingdom

Pushes the switch to its absolute limit, the legend of zelda: tears of the kingdom.

The Legend of Zelda: Breath of the Wild and Tears of the Kingdom boast vibrant art styles that bring Hyrule to life like never before. However, if someone were to focus on the minute details, they might notice reused or flat textures along with large stretches of empty real estate containing nothing but maybe two enemies and a couple of apples. Compared to some other open-world projects, Nintendo's releases might not be that impressive; however, considering the Switch's underpowered hardware, both games are technical marvels.

Tears of the Kingdom gets the nod as it has more content than Breath of the Wild thanks to the implementation of Sky Islands and the Depths. Pushing the Switch to its absolute limit, the sequel delivers one of the most complete and expansive open-world adventures of all time.

The Witcher 3: Wild Hunt

A dark fantasy masterpiece in nearly every way.

Known for being one of the greatest games ever made, CD Projekt Red's The Witcher 3 is phenomenal for numerous reasons. Not all the monsters or gruff characters are a joy to look at because they aren't meant to be, but the sprawling landscapes are constantly killer.

While the console versions look great (not including the Switch port, which is nonetheless impressive in its own right), The Witcher 3 on PC can hit graphical levels that are almost beyond understanding. The game is worth playing for a ton of reasons besides graphics, but looking good is always a plus. The bathtub scene is worth the price of entry alone.

On the right system, Cyberpunk 2077 is also one of the best-looking games ever .

A Plague Tale: Requiem

A proper current-gen experience.

As the ninth console generation picks up steam, more games will debut that raise the bar for graphics, at least on Sony and Microsoft's hardware. A Plague Tale: Requiem is one of the first games to truly come across as a current-gen experience, an achievement aided by Asobo Studio's decision to not produce PS4 and Xbox One versions.

Boasting brilliant facial animations and photo-realistic visuals, Requiem is awe-inspiring on a technical level. While 2019's Innocence is also a pretty game, Requiem far exceeds its predecessor in this department, particularly when it comes to the presentation of the rats.

Forza Horizon 5

Mexico at the player's fingertips.

As long as Forza games continue to be made they will continue to be the best-looking games on the market. Forza Horizon 5 isn't just one of the greatest racing games of the last few years, but one of the most gorgeous titles to ever be released for Xbox.

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While Forza Horizon 4 's British setting resulted in slightly homogenous environments, the sequel's Mexico map is far more diverse, offering 11 biomes that showcase different aspects of the country. While the game looks good on the Xbox One, Forza Horizon 5 is unbelievably gorgeous on PC and the Xbox Series X.

Alan Wake 2

Cinematic quality.

Alan Wake 2 was a long time coming, and the sequel managed to live up to some rather lofty expectations while catering to both returning fans and new players. Split across two campaigns, the story follows Saga as she investigates a murder case that leads her to an unsettling American town with a peculiar populace. In the meantime, Alan finds himself trying to escape the Dark Place, a haunting realm that twists reality into something menacing but familiar.

Although complementary, the two storylines still feel different from each other, and that extends to their detailed and realistic locations. Alan Wake 2 is a technical work of art built using Remedy's own Northlight Engine, which is also responsible for the equally impressive Control and Quantum Break .

Final Fantasy 7 Rebirth

Ambitious, epic, & gorgeous.

Generally, most JRPG franchises tend to trail behind other AAA properties in terms of graphics; however, the one constant exception is Final Fantasy . In most generations, Square Enix produces one or two games that push consoles to their limits – Final Fantasy 6 for the SNES, Final Fantasy 7 and 8 for the PS1, Final Fantasy 12 for the PS2, Final Fantasy 13 for the PS3, and Final Fantasy 7 Remake for the PS4. On the PS5, Final Fantasy 16 and Rebirth are both visually stunning, but the latter gets the nod due to its open-world nature , making for a more impressive final product.

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Set after Cloud and company leave Midgar, Rebirth emphasizes this story's world-spanning nature and scale in a way that could not be done with the 1997 original. Even if the open-world filler content might not be to everyone's tastes, the game is consistently gorgeous, and each region of the map has a unique identity that keeps things interesting. The character and enemy models are unsurprisingly flawless, and they are accompanied by high-quality visual effects that are regularly showcased during the fast-paced combat.

Half-Life: Alyx

The future of gaming.

After more than a decade, Valve finally returned to the Half-Life franchise, albeit with a prequel/sequel rather than a proper third entry. Also, Half-Life: Alyx is a VR game, presumably designed to get people interested in Valve's Index headset. Dropping players in City 17, Alyx not only serves as a showcase of VR technology but is also a proper, substantial addition to the beloved series.

Half-Life: Alyx arguably features the most detailed world in gaming history, and, thanks to virtual reality, one of the most immersive. Although most of the game takes place in underground areas filled with brilliantly designed environments and enemies, Half-Life: Alyx 's presentation goes up another level whenever the story heads to the surface.

Red Dead Redemption 2

An era captured fully.

Red Dead Redemption 2 is arguably the game with the best graphics of all time, although Rockstar's GTA 5 and L.A. Noire would not be bad shouts either. RDR2 is practically a movie due to how detailed and impressive all the NPCs and landscapes look on both consoles and PC.

Not only does every single frame of this adventure look photo-realistic, but RDR2 is also incredibly long and players will never get tired of the scenery . Arthur Morgan looks and feels like a real human being, and the same extends to every other character within the game. RDR2 is nothing short of art.

Groundbreaking Games From Yesteryear

They set the standard.

While not quite as regular of a phenomenon nowadays, the '80s, '90s, and early 2000s produced plenty of games that represented the next leap in graphical prowess. Titles like Pong , Asteroids , Super Mario Bros. , Super Mario 64 , Alone in the Dark , Ocarina of Time , Tomb Raider , Mist , Final Fantasy 7 , and Grand Theft Auto 3 were all visual showcases that changed the industry.

Even if some of these projects' graphics have not aged extremely well, that does not diminish their accomplishments or importance. And, plenty of these masterpieces have stood the test of time, especially Nintendo's SNES-era releases.

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