graphic presentation meaning

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.

• 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.

Suggested Videos

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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Graphical Representation

Graphical representation definition.

Graphical representation refers to the use of charts and graphs to visually display, analyze, clarify, and interpret numerical data, functions, and other qualitative structures. ‍

What is Graphical Representation?

Graphical representation refers to the use of intuitive charts to clearly visualize and simplify data sets. Data is ingested into graphical representation of data software and then represented by a variety of symbols, such as lines on a line chart, bars on a bar chart, or slices on a pie chart, from which users can gain greater insight than by numerical analysis alone. 

Representational graphics can quickly illustrate general behavior and highlight phenomenons, anomalies, and relationships between data points that may otherwise be overlooked, and may contribute to predictions and better, data-driven decisions. The types of representational graphics used will depend on the type of data being explored.

Types of Graphical Representation

Data charts are available in a wide variety of maps, diagrams, and graphs that typically include textual titles and legends to denote the purpose, measurement units, and variables of the chart. Choosing the most appropriate chart depends on a variety of different factors -- the nature of the data, the purpose of the chart, and whether a graphical representation of qualitative data or a graphical representation of quantitative data is being depicted. There are dozens of different formats for graphical representation of data. Some of the most popular charts include:

• Bar Graph -- contains a vertical axis and horizontal axis and displays data as rectangular bars with lengths proportional to the values that they represent; a useful visual aid for marketing purposes
• Choropleth -- thematic map in which an aggregate summary of a geographic characteristic within an area is represented by patterns of shading proportionate to a statistical variable
• Flow Chart -- diagram that depicts a workflow graphical representation with the use of arrows and geometric shapes; a useful visual aid for business and finance purposes
• Heatmap -- a colored, two-dimensional matrix of cells in which each cell represents a grouping of data and each cell’s color indicates its relative value
• Histogram – frequency distribution and graphical representation uses adjacent vertical bars erected over discrete intervals to represent the data frequency within a given interval; a useful visual aid for meteorology and environment purposes
• Line Graph – displays continuous data; ideal for predicting future events over time;  a useful visual aid for marketing purposes
• Pie Chart -- shows percentage values as a slice of pie; a useful visual aid for marketing purposes
• Pointmap -- CAD & GIS contract mapping and drafting solution that visualizes the location of data on a map by plotting geographic latitude and longitude data
• Scatter plot -- a diagram that shows the relationship between two sets of data, where each dot represents individual pieces of data and each axis represents a quantitative measure
• Stacked Bar Graph -- a graph in which each bar is segmented into parts, with the entire bar representing the whole, and each segment representing different categories of that whole; a useful visual aid for political science and sociology purposes
• Timeline Chart -- a long bar labelled with dates paralleling it that display a list of events in chronological order, a useful visual aid for history charting purposes
• Tree Diagram -- a hierarchical genealogical tree that illustrates a family structure; a useful visual aid for history charting purposes
• Venn Diagram -- consists of multiple overlapping usually circles, each representing a set; the default inner join graphical representation

Proprietary and open source software for graphical representation of data is available in a wide variety of programming languages. Software packages often provide spreadsheets equipped with built-in charting functions.

Advantages and Disadvantages of Graphical Representation of Data

Tabular and graphical representation of data are a vital component in analyzing and understanding large quantities of numerical data and the relationship between data points. Data visualization is one of the most fundamental approaches to data analysis, providing an intuitive and universal means to visualize, abstract, and share complex data patterns. The primary advantages of graphical representation of data are:

• Facilitates and improves learning: graphics make data easy to understand and eliminate language and literacy barriers
• Understanding content: visuals are more effective than text in human understanding
• Flexibility of use: graphical representation can be leveraged in nearly every field involving data
• Increases structured thinking: users can make quick, data-driven decisions at a glance with visual aids
• Supports creative, personalized reports for more engaging and stimulating visual  presentations 
• Improves communication: analyzing graphs that highlight relevant themes is significantly faster than reading through a descriptive report line by line
• Shows the whole picture: an instantaneous, full view of all variables, time frames, data behavior and relationships

Disadvantages of graphical representation of data typically concern the cost of human effort and resources, the process of selecting the most appropriate graphical and tabular representation of data, greater design complexity of visualizing data, and the potential for human bias.

Why Graphical Representation of Data is Important

Graphic visual representation of information is a crucial component in understanding and identifying patterns and trends in the ever increasing flow of data. Graphical representation enables the quick analysis of large amounts of data at one time and can aid in making predictions and informed decisions. Data visualizations also make collaboration significantly more efficient by using familiar visual metaphors to illustrate relationships and highlight meaning, eliminating complex, long-winded explanations of an otherwise chaotic-looking array of figures. 

Data only has value once its significance has been revealed and consumed, and its consumption is best facilitated with graphical representation tools that are designed with human cognition and perception in mind. Human visual processing is very efficient at detecting relationships and changes between sizes, shapes, colors, and quantities. Attempting to gain insight from numerical data alone, especially in big data instances in which there may be billions of rows of data, is exceedingly cumbersome and inefficient.

Does HEAVY.AI Offer a Graphical Representation Solution?

HEAVY.AI's visual analytics platform is an interactive data visualization client that works seamlessly with server-side technologies HEAVY.AIDB and Render to enable data science analysts to easily visualize and instantly interact with massive datasets. Analysts can interact with conventional charts and data tables, as well as big data graphical representations such as massive-scale scatterplots and geo charts. Data visualization contributes to a broad range of use cases, including performance analysis in business and guiding research in academia.

• Math Article

Graphical Representation

Graphical Representation is a way of analysing numerical data. It exhibits the relation between data, ideas, information and concepts in a diagram. It is easy to understand and it is one of the most important learning strategies. It always depends on the type of information in a particular domain. There are different types of graphical representation. Some of them are as follows:

• Line Graphs – Line graph or the linear graph is used to display the continuous data and it is useful for predicting future events over time.
• Bar Graphs – Bar Graph is used to display the category of data and it compares the data using solid bars to represent the quantities.
• Histograms – The graph that uses bars to represent the frequency of numerical data that are organised into intervals. Since all the intervals are equal and continuous, all the bars have the same width.
• Line Plot – It shows the frequency of data on a given number line. ‘ x ‘ is placed above a number line each time when that data occurs again.
• Frequency Table – The table shows the number of pieces of data that falls within the given interval.
• Circle Graph – Also known as the pie chart that shows the relationships of the parts of the whole. The circle is considered with 100% and the categories occupied is represented with that specific percentage like 15%, 56%, etc.
• Stem and Leaf Plot – In the stem and leaf plot, the data are organised from least value to the greatest value. The digits of the least place values from the leaves and the next place value digit forms the stems.
• Box and Whisker Plot – The plot diagram summarises the data by dividing into four parts. Box and whisker show the range (spread) and the middle ( median) of the data.

General Rules for Graphical Representation of Data

There are certain rules to effectively present the information in the graphical representation. They are:

• Suitable Title: Make sure that the appropriate title is given to the graph which indicates the subject of the presentation.
• Measurement Unit: Mention the measurement unit in the graph.
• Proper Scale: To represent the data in an accurate manner, choose a proper scale.
• Index: Index the appropriate colours, shades, lines, design in the graphs for better understanding.
• Data Sources: Include the source of information wherever it is necessary at the bottom of the graph.
• Keep it Simple: Construct a graph in an easy way that everyone can understand.
• Neat: Choose the correct size, fonts, colours etc in such a way that the graph should be a visual aid for the presentation of information.

Graphical Representation in Maths

In Mathematics, a graph is defined as a chart with statistical data, which are represented in the form of curves or lines drawn across the coordinate point plotted on its surface. It helps to study the relationship between two variables where it helps to measure the change in the variable amount with respect to another variable within a given interval of time. It helps to study the series distribution and frequency distribution for a given problem.  There are two types of graphs to visually depict the information. They are:

• Time Series Graphs – Example: Line Graph
• Frequency Distribution Graphs – Example: Frequency Polygon Graph

Principles of Graphical Representation

Algebraic principles are applied to all types of graphical representation of data. In graphs, it is represented using two lines called coordinate axes. The horizontal axis is denoted as the x-axis and the vertical axis is denoted as the y-axis. The point at which two lines intersect is called an origin ‘O’. Consider x-axis, the distance from the origin to the right side will take a positive value and the distance from the origin to the left side will take a negative value. Similarly, for the y-axis, the points above the origin will take a positive value, and the points below the origin will a negative value.

Generally, the frequency distribution is represented in four methods, namely

• Smoothed frequency graph
• Pie diagram
• Cumulative or ogive frequency graph
• Frequency Polygon

Merits of Using Graphs

Some of the merits of using graphs are as follows:

• The graph is easily understood by everyone without any prior knowledge.
• It saves time
• It allows us to relate and compare the data for different time periods
• It is used in statistics to determine the mean, median and mode for different data, as well as in the interpolation and the extrapolation of data.

Example for Frequency polygonGraph

Here are the steps to follow to find the frequency distribution of a frequency polygon and it is represented in a graphical way.

• Obtain the frequency distribution and find the midpoints of each class interval.
• Represent the midpoints along x-axis and frequencies along the y-axis.
• Plot the points corresponding to the frequency at each midpoint.
• Join these points, using lines in order.
• To complete the polygon, join the point at each end immediately to the lower or higher class marks on the x-axis.

Draw the frequency polygon for the following data

Mark the class interval along x-axis and frequencies along the y-axis.

Let assume that class interval 0-10 with frequency zero and 90-100 with frequency zero.

Now calculate the midpoint of the class interval.

Using the midpoint and the frequency value from the above table, plot the points A (5, 0), B (15, 4), C (25, 6), D (35, 8), E (45, 10), F (55, 12), G (65, 14), H (75, 7), I (85, 5) and J (95, 0).

To obtain the frequency polygon ABCDEFGHIJ, draw the line segments AB, BC, CD, DE, EF, FG, GH, HI, IJ, and connect all the points.

Frequently Asked Questions

What are the different types of graphical representation.

Some of the various types of graphical representation include:

• Line Graphs
• Frequency Table
• Circle Graph, etc.

Read More:  Types of Graphs

What are the Advantages of Graphical Method?

Some of the advantages of graphical representation are:

• It makes data more easily understandable.
• It saves time.
• It makes the comparison of data more efficient.

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Very useful for understand the basic concepts in simple and easy way. Its very useful to all students whether they are school students or college sudents

Thanks very much for the information

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How to Use Visual Communication: Definition, Examples, Templates

By Midori Nediger , Aug 27, 2020

With so many businesses and organizations now operating online, visual communication is more important than ever.

Whether you’re an executive looking to align your team on new organizational processes, or a marketer looking for ways to differentiate on social media, you may wonder how best to use visuals to really connect with your audience.

In this guide, I’ll give you some trade secrets from my experience as an information designer. I’ll show you how to leverage design and visual communications best practices to engage your audience while avoiding information overload.

Table of contents:

• What is visual communication?

What are some of the most common types of visual communication?

Why does visual communication matter, how to use visual communication in the workplace, how to make your visual communications look professional, what is visual communication visual communication defined:.

Visual communication is the practice of using visual elements to convey a message, inspire change, or evoke emotion. 

It’s one part communication design— crafting a message that educates, motivates, and engages,  and one part graphic design— using design principles to communicate that message so that it’s clear and eye-catching.

Effective visual communication should be equally appealing and informative.

Visual communication is really about picking the right elements (usually text, icons, shapes, imagery and data visualizations) to create meaning for your audience.  You can also communicate visually with video. For example, you can use a free screen recorder to show a colleague how to complete a task rather than sharing a document.

Some common visual communication strategies include:

• Using data visualization to show the impact of your work
• Using shapes and lines to outline relationships, processes, and flows
• Using symbols and icons to make information more memorable
• Using visuals and data to tell stories  
• Using color to indicate importance and draw attention

When you think about visual communication, your mind might first jump to design-heavy content like social media graphics or infographics .

And while visual communication certainly plays a role in those cases, there are a ton of other types of content that fall under the visual communication umbrella.

Some common types of visual communications in the workplace include:

• Process Diagrams
• Flow Charts
• Charts and Graphs
• Visual Reports
• Presentations

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These can look very different when used in different industries, but they all use the same visual communication strategies and design principles to accurately present information and create meaning for audiences.

Let’s take a look at some visual communication strategies used across different types of organizations.

Nonprofit organizations

Nonprofit organizations often combine data visualization and visual storytelling to gain the trust of their audiences and establish the credibility of their organization. 

This might take the form of a statistical infographic or an impact report that they share with their donors and supporters:

They may also create public-facing informational posters or brochures to build awareness around their organization and foster support for their cause. 

Another place where visual communication is key for larger nonprofits is to update stakeholders on campaign or research results. These reports often combine storytelling with data visualization to inform and convince. 

Healthcare organizations

A visual communication strategy often applied in healthcare is the use of plain language and simple iconography to communicate with audiences with lower health literacy. 

For example, a public health unit might create an infographic factsheet to ensure that recommended protocols are followed, like these recent COVID-19 guidelines from Public Health Ontario:

In fact, the CDC recommends the use of visuals to boost understanding of health information for external communications in healthcare.

These types of visual guides aren’t just helpful for external communication. Similar tactics can be used to remind staff of workplace best practices, like patient safety and infection prevention practices.

Learn more: Venngage for Healthcare Organizations

Business consulting organizations

Business development organizations may use diagrams like process maps to communicate high-level strategy to clients , which can help make their value more tangible.

A simple roadmap or summary of strategy recommendations can go a long way towards communicating and aligning with clients.

Visuals can help create understanding where words alone cannot. 

They can help bridge the gap between concepts and words, especially when appealing to an audience with diverse needs and backgrounds.

It’s clear that visual communication is top-of-mind for many. When we surveyed marketers about their use of visual content , 74% of the marketers we surveyed stated that more than 70% of their content contained some form of visual.

Plus, it’s been demonstrated time and time again that in addition to making information more engaging, visuals can actually help with the comprehension of information. 

But when should you consider making your content more visual?

You can use visual communication to:

• Engage your audience
• Communicate complex information
• Tell a story and convey emotion
• Simplify information
• Communicate the impact of your data

Let’s take a look at how this can apply in the workplace.

You might think that visual communication isn’t really necessary in your day-to-day work. 

But visuals, in the right hands, can be used as a tool to influence what your audience pays attention to, thinks about, and understands. 

1. How to make boring topics engaging

Creating engaging content that shows the value of your business can be a challenge when you work in a “boring” or technical industry like finance, business development, engineering or healthcare.

But it’s this kind of challenge where visual communication shines. Creating unique visuals can help you position yourself as the innovative solution in the market.

Here are some simple strategies to consider:

Use stylized icons to make technical information feel concrete and approachable

This infographic about credit card merchant processing, for example, takes advantage of a playful icon style and a modern design treatment to capture your attention and keep you reading.

This might be the perfect way to signal to young business owners that you’re different from the traditional big banks, and that you’re right for them. It feels so much more approachable than a wall of text on a web page.

Just applying some basic visual communication strategies can make this “boring” technical information a bit more accessible and relatable to your target audience —ready to boost engagement on social media, your blog, or your newsletter.

Use visual metaphors to get your audience thinking

Visual metaphors are another way to make old ideas feel fresh and exciting, and can even help foster deeper understanding of your subject matter.

The use of women running in the infographic below, for example, helps me think about NPS scores in a new way:

By allowing the visual presentation to drive how you position the value of your product or service, you can find new ways to reach your customers.

Read more: Common symbols and meanings and how to use them in design

To sum up, here are some visual communication tips for how to make boring topics engaging:

• Use visuals and icons to make technical information feel approachable
• Choose a graphic design style that will resonate with your target audience 
• Think outside of the box: use a unique visual presentation to get your audience thinking 

If your visual presentation is unique, your information doesn’t have to be revolutionary to give you an edge over your competitors.

Read more: Infographic ideas to make your information engaging.

2. How to communicate process changes and improvements

Being able to quickly re-align your team on process changes has never been more important. 

Visuals can make processes easier to understand and more memorable. They can also help boost employee alignment and engagement. 

Here’s how you can use process documentation to help align your team.

Show both high-level and low-level changes with hierarchical process diagrams

Breaking down processes into discrete visual steps can make new processes much easier to grasp.

And breaking down steps into even smaller sections can help you communicate both high-level concepts and specific details in the same place, like in this process diagram below.

Providing these process documents to employees can help quickly align teams on new strategies, like an action plan to address a crisis or a shift into a new market, while also acting as a reference point in the future.

• Provide presentation slides as a post-meeting reference guide 

With remote work becoming the norm, you likely spend many of your days in back-to-back Zoom calls. 

If you’re holding a meeting to discuss major process changes or company updates, it may be worth your while to whip up some quick meeting slides to help clarify changes and ensure your team is aligned.

Including a slide deck can help reinforce the importance of what’s discussed, and act as a reference when your team digs into their work.

Provide checklists to help your team keep track of complex processes

Providing a checklist of steps for your team to follow can help you delegate work with confidence, while giving your team the confidence to know that they’re doing things right.

Checklists are particularly helpful for communicating complex or proprietary internal processes, as they can help remove any anxiety from the process.

Build out a library of internal training documents that you can update periodically

Building out a library of training documents, while it might take a bit of time up front, can really save time and money in the long run, because a team that’s aligned is a team that’s productive.

Onboarding guides, FAQs for new employees (like the fun onboarding FAQs below), and other process documentation can all help make remote onboarding easier, and help new employees feel comfortable and in control.

HR onboarding checklists can help avoid the headache of overlooked paperwork and unclear expectations. Having one checklist for the employee and one for your HR department will help keep everyone aligned and on top of their tasks.

If you’re ramping up to hire a mass of new employees, it may even be worth rethinking the design of your offer letter . After your new employee signs, you can send on their package of matching onboarding documents.

And once you create those documents, they should be easy to update and disseminate to new and existing team members, making your job even easier.

To summarize, here are your tips for communicating process changes on the fly:

• Show high- and low-level changes with hierarchical process diagrams
• Help your team keep track of changes with checklists
• Build a library of internal training documents that you can update periodically

3. How to simplify complex information with visuals

Perhaps the most powerful use of visual communication is to simplify complex information. 

Just take this image that HubSpot posted on Twitter recently, for example. With one simple visual, they manage to position their product as the perfect solution to three problems experienced across three different teams:

This doesn’t just work for external communications on social media.

It can be the perfect approach for consultants looking to communicate their ideas and strategies to clients, in a quick and digestible way.

Or B2B organizations in technical fields looking to demystify the products and services they offer to differentiate from their competitors, without using a ton of technical language:

Or healthcare organizations looking to make recommendations clear to patients:

The four key steps for simplifying complex information with visuals are:

• Remove as much text as possible
• Use shapes like circles and rectangles to indicate groupings
• Use lines and borders to indicate flows and relationships
• Use color and size to draw attention to key information

Read More: How to Summarize Information Visually

4. How to visualize data and insights

Effective data visualization does more than just display some data from a spreadsheet.

It should communicate insights and capture ideas. It should communicate the why behind the trends.

It should help you answer the question often asked by busy people with competing demands: why should I care?

• Use the right chart for your data and your goal

The first thing to consider when visualizing data is what visual form will best communicate your insight.

At Venngage, we’ve developed the ICCOR method to help you choose the best charts for your infographic. The ICCOR method is a framework aimed to help you use a visualization type that aligns with your communication goal.

Your communication goal might be to: 

• Inform : convey a single important message or data point that doesn’t require much context to understand
• Compare : show similarities or differences among values or parts of a whole
• Show Change : visualize trends over time or space
• Organize : show groups, patterns, rank or order
• Reveal Relationships : show correlations among variables or values

Each of these different goals will be best communicated with a different type of chart.

For example, icons arrays (also called ‘pictograms’) have been shown to be more effective than bar or pie charts for communicating risk , which is particularly important for healthcare providers and public health workers who want to support good decision making in their patients.

Bar charts, on the other hand, are perfect for handling larger amounts of data and highlighting comparisons between sets of data, which might be more important for those working in finance:

For access to professional templates, and a simple editor to visualize financial information, check out: Venngage for Finance

For the full ICCOR framework, check out: How to choose the best types of charts for your data

Choosing a chart is just one part of the process. How do you actually make an impact with your data?

• Tell a story with your data to inspire your audience

A plain old bar graph won’t do much to inspire your audience. But a creative combination of charts, visuals, text, and statistics that tells a story can. 

By highlighting the right numbers and pulling in text and other visuals, you can show the impact of your organization in a more holistic way, and tell the story behind the data.

Storytelling with data is as much about crafting a narrative as it is about understanding and communicating the insights in your data. 

The first step to crafting your narrative is understanding your audience. Think about:

• What’s going on in their lives?
• What knowledge do they have on the subject?
• What context do they need from you?

Once you understand your audience, it should be easy to pull out the insights that will make an impact, and present them in an impactful way. That’s the difference between an engaging design and your standard Excel chart.

Another common practice in data storytelling is the use of icon stories to draw viewers in and make abstract ideas more concrete.

Take this report from UNICEF, for example. The simple, universal icons are combined in different ways to create and reinforce key ideas, creating an impactful report that will be memorable for readers.

• Call out key insights and action items in the data

The impact of your hard work can easily get lost in a monthly or quarterly report. 

But you can apply the design techniques typically used in infographics to make sure your efforts stand out of more traditional summative reports.

The trick is to do more with less. Get rid of data that doesn’t say anything, and emphasize the data that’s meaningful. Remove the noise to pull focus towards what’s useful.

Highlight key data points and add annotations to provide context to the most important data:

Here’s what to consider when visualizing your data and insights:

• Understand your audience and design with their knowledge in mind

Read more: Data visualization examples and best practices

If you’re not a full-time designer, one of your main concerns might be making sure your visual communications look professional. 

You want to make sure you’re producing content that elevates your brand, and inspires your colleagues, donors, and stakeholders.

Here’s what you should think about:

Establish a cohesive visual brand for any external communications

It’s critical for any growing business to establish cohesive visual branding. 

Especially for consumer-facing communications, like for your blog or social media, the quality of your visual brand signals to your customers about the quality of your organization.

Luckily, it’s pretty easy to ensure your branding feels consistent. Here’s how:

• Include the same header and footer with your logo across infographics, one-pagers, reports, and flyers
• Apply your brand fonts and colors consistently across all of your collateral
• Use the same style of symbols and icons across every document

As a shortcut, you can use Venngage’s Brand Kit to add your brand logos, fonts and colors to your designs with just a few clicks.

Read more: Don’t have your brand guidelines built out yet? Learn how to choose fonts and how to pick colors for designs, first.

Repurpose and reuse designs to keep your communications consistent

Reusing and repurposing existing designs can truly be a game changer.

For one, it’ll speed up your workflow. But more importantly, it’ll ensure that you’re producing communications that are consistent and cohesive.

Did I mention yet that your communications need to be cohesive?

You can repurpose the documents you’ve created for one client or project, add different content and tweak it a bit for a new client or a different target audience, to get a ton of mileage out of a small amount of design work.

Even if you’re just creating documents to share internally, like project summaries or company newsletters, you can set yourself and your team apart by producing documents that have a consistent visual style.

The recent rapid transition to remote work has propelled visual communication from a “nice-to-have” into an integral part of communication at work. 

I hope you’ve already started thinking about how you can use visuals to amplify your communications. 

Just remember to keep these design and visual communication principles in mind:

• Use modern design and visuals to make boring information engaging and differentiate yourself from your competitors
• Simplify your information to make an impact
• Use data visualization techniques to show the value of your work
• Create designs with a cohesive visual brand and reuse them to keep your communications consistent

For help getting started with visual communication and infographics, check out this guide: How to make an infographic in 5 steps .

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.

• Using literature reviews to strengthen research: tips for PhDs and supervisors
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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 .

If you found this interesting and want advice and insight from academics and university staff delivered direct to your inbox each week,  sign up for the THE Campus newsletter .

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2: Graphical Representations of Data

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In this chapter, you will study numerical and graphical ways to describe and display your data. This area of statistics is called "Descriptive Statistics." You will learn how to calculate, and even more importantly, how to interpret these measurements and graphs.

• 2.1: Introduction In this chapter, you will study numerical and graphical ways to describe and display your data. This area of statistics is called "Descriptive Statistics." You will learn how to calculate, and even more importantly, how to interpret these measurements and graphs. In this chapter, we will briefly look at stem-and-leaf plots, line graphs, and bar graphs, as well as frequency polygons, and time series graphs. Our emphasis will be on histograms and box plots.
• 2.2: Stem-and-Leaf Graphs (Stemplots), Line Graphs, and Bar Graphs A stem-and-leaf plot is a way to plot data and look at the distribution, where all data values within a class are visible. The advantage in a stem-and-leaf plot is that all values are listed, unlike a histogram, which gives classes of data values. A line graph is often used to represent a set of data values in which a quantity varies with time. These graphs are useful for finding trends.  A bar graph is a chart that uses either horizontal or vertical bars to show comparisons among categories.
• 2.3: Histograms, Frequency Polygons, and Time Series Graphs A histogram is a graphic version of a frequency distribution. The graph consists of bars of equal width drawn adjacent to each other. The horizontal scale represents classes of quantitative data values and the vertical scale represents frequencies. The heights of the bars correspond to frequency values. Histograms are typically used for large, continuous, quantitative data sets. A frequency polygon can also be used when graphing large data sets with data points that repeat.
• 2.4: Using Excel to Create Graphs Using technology to create graphs will make the graphs faster to create, more precise, and give the ability to use larger amounts of data. This section focuses on using Excel to create graphs.
• 2.5: Graphs that Deceive It's common to see graphs displayed in a misleading manner in social media and other instances. This could be done purposefully to make a point, or it could be accidental. Either way, it's important to recognize these instances to ensure you are not misled.
• 2.E: Graphical Representations of Data (Exercises) These are homework exercises to accompany the Textmap created for "Introductory Statistics" by OpenStax.

Contributors and Attributions

Barbara Illowsky and Susan Dean (De Anza College) with many other contributing authors. Content produced by OpenStax College is licensed under a Creative Commons Attribution License 4.0 license. Download for free at http://cnx.org/contents/[email protected] .

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• Graphs and Graphical Representation

What are Graphs and Graphical Representation?

Graphical representation refers to the use of charts and graphs to visually analyze and display, interpret numerical value, clarify the qualitative structures. The data is represented by a variety of symbols such as line charts, bars, circles, ratios. Through this, greater insight is stuck in the mind while analyzing the information. 

Graphs can easily illustrate the behavior, highlight changes, and can study data points that may sometimes be overlooked. The type of data presentation depends upon the type of data being used. 

Graphical Representation of Data

The graphical representation is simply a way of analyzing numerical data. It comprises a relation between data, information, and ideas in a diagram. Anything portrayed in a graphical manner is easy to understand and is also termed as the most important learning technique. The graphical presentation is always dependent on the type of information conveyed. There are different types of graphical representation. These are as follows:

Line Graphs: 

Also denoted as linear graphs are used to examine continuous data and are also useful in predicting future events in time.

Histograms: 

This graph uses bars to represent the information. The bars represent the frequency of numerical data. All intervals are equal and hence, the width of each bar is also equal.

Bar Graphs: 

These are used to display the categories and compare the data using solid bars. These bars represent the quantities.

Frequency Table: 

This table shows the frequency of data that falls within that given time interval. 

Line Plot: 

It shows the frequency of data on a given line number.

Circle Graph: 

It is also known as a pie chart and shows the relationship between the parts of the whole. The circle consists of 100% and other parts shown are in different proportions.

Scatter Plot: 

The diagram shows the relationship between two sets of data. Each dot represents individual information of the data.

Venn Diagram: 

It consists of overlapping circles, each depicting a set. The inner-circle made is a graphical representation.

Stem and Leaf Plot: 

The data is organized from the least value to the highest value. The digits of the least place value form the leaf and that of the highest place value form the stem.

 Box and Whisker Plot: 

The data is summarised by dividing it into four parts. Box and whisker show the spread and median of the data.

Graphical Presentation of Data - Definition

It is a way of analyzing numerical data. It is a sort of chart which shows statistical data in the form of lines or curves which are plotted on the surface. It enables studying the cause and effect relationships between two variables . It helps to measure the extent of change in one variable when another variable changes. 

Principles of Graphical Representation

The variables in the graph are represented using two lines called coordinate axes. The horizontal and vertical axes are denoted by x and y respectively. Their point of intersection is called an origin ‘O’. Considering x-axes, the distance from the origin to the right will take a positive value, and the distance from the origin to the left will take a negative value. Taking the same procedure on y-axes. The points above origin will take the positive values and the points below origin will take negative values. As discussed in the earlier section about the types of graphical representation. There are four most widely used graphs namely histogram, pie diagram, frequency polygon, and ogive frequency graph.

Rules for Graphical Representation of Data

There are certain rules to effectively represent the information in graphical form. Certain rules are discussed below:

Title: One has to make sure that a suitable title is given to the graph which indicates the presentation subject.

Scale: It should be used efficiently to represent data in an accurate manner.

Measurement unit: It is used to calculate the distance between the box

Index: Differentiate appropriate colors, shades, and design I graph for a better understanding of the information conveyed.

Data sources: Include the source of information at the bottom graph wherever necessary. It adds to the authenticity of the information. 

Keep it simple: Construct the graph in an easy to understand manner and keep it simple for the reader to understand. Looking at the graph the information portrayed is easily understandable. 

Importance of Graphical Representation of Data

Some of the importance and advantages of using graphs to interpret data are listed below:

The graph is easiest to understand as the information portrayed is in facts and figures. Any information depicted in facts, figures, comparison grabs our attention, due to which they are memorizable for the long term.

It allows us to relate and compare data for different time periods.

It is used in statistics to determine the mean , mode, and median of different data.

It saves a lot of time as it covers most of the information in facts and figures. This in turn compacts the information.

FAQs on Graphs and Graphical Representation

Q1. State the Advantages and Disadvantages of Graphical Representation of Data?

Ans: These graphical presentations of data are vital components in analyzing the information. Data visualization is one of the most fundamental approaches to data representation. Its advantages include the following points:

Facilitates and improves learning

Flexibility of use

Understands content

Increase structure thinking

Supports creative thinking

Portrays the whole picture

Improves communication

With advantages, certain disadvantages are also linked to the graphical representation. The disadvantages concern the high cost of human effort, the process of selecting the most appropriate graphical and tabular presentation, creative thinking, greater design to interpret information, visualizing data, and as human resource is used. The potential for human bias plays a huge role.

Q2. What is the Graphical Representation of Data in Statistics?

Graphs are powerful data evaluation tools. They provide a quick visual summary of the information. In statistics information depicted is of mean, mode, and median. Box plots, histograms are used to depict the information. These graphs provide information about ranges, shapes, concentration, extreme values, etc. It studies information between different sets and trends whether increasing or decreasing. Since graphical methods are qualitative, they are not only the basis of comparison and information.

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Graphical Methods – Types, Examples and Guide

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Graphical Methods

Definition:

Graphical methods refer to techniques used to visually represent data, relationships, or processes using charts, graphs, diagrams, or other graphical formats. These methods are widely used in various fields such as science, engineering, business, and social sciences, among others, to analyze, interpret and communicate complex information in a concise and understandable way.

Types of Graphical Methods

Here are some of the most common types of graphical methods for data analysis and visual presentation:

Line Graphs

These are commonly used to show trends over time, such as the stock prices of a particular company or the temperature over a certain period. They consist of a series of data points connected by a line that shows the trend of the data over time. Line graphs are useful for identifying patterns in data, such as seasonal changes or long-term trends.

These are commonly used to compare values of different categories, such as sales figures for different products or the number of students in different grade levels. Bar charts use bars that are either horizontal or vertical and represent the data values. They are useful for comparing data visually and identifying differences between categories.

These are used to show how a whole is divided into parts, such as the percentage of students in a school who are enrolled in different programs. Pie charts use a circle that is divided into sectors, with each sector representing a portion of the whole. They are useful for showing proportions and identifying which parts of a whole are larger or smaller.

Scatter Plots

These are used to visualize the relationship between two variables, such as the correlation between a person’s height and weight. Scatter plots consist of a series of data points that are plotted on a graph and connected by a line or curve. They are useful for identifying trends and relationships between variables.

These are used to show the distribution of data across a two-dimensional plane, such as a map of a city showing the density of population in different areas. Heat maps use color-coded cells to represent different levels of data, with darker colors indicating higher values. They are useful for identifying areas of high or low density and for highlighting patterns in data.

These are used to show the distribution of data in a single variable, such as the distribution of ages of a group of people. Histograms use bars that represent the frequency of each data value, with taller bars indicating a higher frequency. They are useful for identifying the shape of a distribution and for identifying outliers or unusual data values.

Network Diagrams

These are used to show the relationships between different entities or nodes, such as the relationships between people in a social network. Network diagrams consist of nodes that are connected by lines that represent the relationship. They are useful for identifying patterns in complex data and for understanding the structure of a network.

Box plots, also known as box-and-whisker plots, are a type of graphical method used to show the distribution of data in a single variable. They consist of a box with whiskers extending from the top and bottom of the box. The box represents the middle 50% of the data, with the median value indicated by a line inside the box. The whiskers represent the range of the data, with any data points outside the whiskers indicated as outliers. Box plots are useful for identifying the spread and shape of a distribution and for identifying outliers or unusual data values.

Applications of Graphical Methods

Graphical methods have a wide range of applications in various fields, including:

• Business : Graphical methods are commonly used in business to analyze sales data, financial data, and other types of data. They are useful for identifying trends, patterns, and outliers, as well as for presenting data in a clear and concise manner to stakeholders.
• Science and engineering: Graphical methods are used extensively in scientific and engineering fields to analyze data and to present research findings. They are useful for visualizing complex data sets and for identifying relationships between variables.
• Social sciences: Graphical methods are used in social sciences to analyze and present data related to human behavior, such as demographics, survey results, and statistical analyses. They are useful for identifying trends and patterns in large data sets and for communicating findings to a broader audience.
• Education : Graphical methods are used in education to present information to students and to help them understand complex concepts. They are useful for visualizing data and for presenting information in a way that is easy to understand.
• Healthcare : Graphical methods are used in healthcare to analyze patient data, to track disease outbreaks, and to present medical information to patients. They are useful for identifying patterns and trends in patient data and for communicating medical information in a clear and concise manner.
• Sports : Graphical methods are used in sports to analyze and present data related to player performance, team statistics, and game outcomes. They are useful for identifying trends and patterns in player and team data and for communicating this information to coaches, players, and fans.

Examples of Graphical Methods

Here are some examples of real-time applications of graphical methods:

• Stock Market: Line graphs, candlestick charts, and bar charts are widely used in real-time trading systems to display stock prices and trends over time. Traders use these charts to analyze historical data and make informed decisions about buying and selling stocks in real-time.
• Weather Forecasting : Heat maps and radar maps are commonly used in weather forecasting to display current weather conditions and to predict future weather patterns. These maps are useful for tracking the movement of storms, identifying areas of high and low pressure, and predicting the likelihood of severe weather events.
• Social Media Analytics: Scatter plots and network diagrams are commonly used in social media analytics to track the spread of information across social networks. Analysts use these graphs to identify patterns in user behavior, to track the popularity of specific topics or hashtags, and to monitor the influence of key opinion leaders.
• Traffic Analysis: Heat maps and network diagrams are used in traffic analysis to visualize traffic flow patterns and to identify areas of congestion or accidents. These graphs are useful for predicting traffic patterns, optimizing traffic flow, and improving transportation infrastructure.
• Medical Diagnostics: Box plots and histograms are commonly used in medical diagnostics to display the distribution of patient data, such as blood pressure, heart rate, or blood sugar levels. These graphs are useful for identifying patterns in patient data, diagnosing medical conditions, and monitoring the effectiveness of treatments in real-time.
• Cybersecurity: Heat maps and network diagrams are used in cybersecurity to visualize network traffic patterns and to identify potential security threats. These graphs are useful for identifying anomalies in network traffic, detecting and mitigating cyber attacks, and improving network security protocols.

How to use Graphical Methods

Here are some general steps to follow when using graphical methods to analyze and present data:

• Identify the research question: Before creating any graphs, it’s important to identify the research question or hypothesis you want to explore. This will help you select the appropriate type of graph and ensure that the data you collect is relevant to your research question.
• Collect and organize the data: Collect the data you need to answer your research question and organize it in a way that makes it easy to work with. This may involve sorting, filtering, or cleaning the data to ensure that it is accurate and relevant.
• Select the appropriate graph : There are many different types of graphs available, each with its own strengths and weaknesses. Select the appropriate graph based on the type of data you have and the research question you are exploring. For example, a scatterplot may be appropriate for exploring the relationship between two continuous variables, while a bar chart may be appropriate for comparing categorical data.
• Create the graph: Once you have selected the appropriate graph, create it using software or a tool that allows you to customize the graph based on your needs. Be sure to include appropriate labels and titles, and ensure that the graph is clearly legible.
• Analyze the graph: Once you have created the graph, analyze it to identify patterns, trends, and relationships in the data. Look for outliers or other anomalies that may require further investigation.
• Draw conclusions: Based on your analysis of the graph, draw conclusions about the research question you are exploring. Use the graph to support your conclusions and to communicate your findings to others.
• Iterate and refine: Finally, refine your graph or create additional graphs as needed to further explore your research question. Iteratively refining and revising your graphs can help to ensure that you are accurately representing the data and that you are drawing the appropriate conclusions.

When to use Graphical Methods

Graphical methods can be used in a variety of situations to help analyze, interpret, and communicate data. Here are some general guidelines on when to use graphical methods:

• To identify patterns and trends: Graphical methods are useful for identifying patterns and trends in data, which may be difficult to see in raw data tables or spreadsheets. Graphs can reveal trends that may not be immediately apparent in the data, making it easier to draw conclusions and make predictions.
• To compare data: Graphs can be used to compare data from different sources or over different time periods. Graphical comparisons can make it easier to identify differences or similarities in the data, which can be useful for making decisions and taking action.
• To summarize data : Graphs can be used to summarize large amounts of data in a single visual display. This can be particularly useful when presenting data to a broad audience, as it can help to simplify complex data sets and make them more accessible.
• To communicate data: Graphs can be used to communicate data and findings to a variety of audiences, including stakeholders, colleagues, and the general public. Graphs can be particularly useful in situations where data needs to be presented quickly and in a way that is easy to understand.
• To identify outliers: Graphical methods are useful for identifying outliers or anomalies in the data. Outliers can be indicative of errors or unusual events, and may warrant further investigation.

Purpose of Graphical Methods

The purpose of graphical methods is to help people analyze, interpret, and communicate data in a way that is both accurate and understandable. Graphical methods provide visual representations of data that can be easier to interpret than tables of numbers or raw data sets. Graphical methods help to reveal patterns and trends that may not be immediately apparent in the data, making it easier to draw conclusions and make predictions. They can also help to identify outliers or unusual data points that may warrant further investigation.

In addition to helping people analyze and interpret data, graphical methods also serve an important communication function. Graphs can be used to present data to a wide range of audiences, including stakeholders, colleagues, and the general public. Graphs can help to simplify complex data sets, making them more accessible and easier to understand. By presenting data in a clear and concise way, graphical methods can help people make informed decisions and take action based on the data.

Overall, the purpose of graphical methods is to provide a powerful tool for analyzing, interpreting, and communicating data. Graphical methods help people to better understand the data they are working with, to identify patterns and trends, and to make informed decisions based on the data.

Characteristics of Graphical Methods

Here are some characteristics of graphical methods:

• Visual Representation: Graphical methods provide a visual representation of data, which can be easier to interpret than tables of numbers or raw data sets. Graphs can help to reveal patterns and trends that may not be immediately apparent in the data.
• Simplicity : Graphical methods simplify complex data sets, making them more accessible and easier to understand. By presenting data in a clear and concise way, graphical methods can help people make informed decisions and take action based on the data.
• Comparability : Graphical methods can be used to compare data from different sources or over different time periods. This can help to identify differences or similarities in the data, which can be useful for making decisions and taking action.
• Flexibility : Graphical methods can be adapted to different types of data, including continuous, categorical, and ordinal data. Different types of graphs can be used to display different types of data, depending on the characteristics of the data and the research question.
• Accuracy : Graphical methods should accurately represent the data being analyzed. Graphs should be properly scaled and labeled to avoid distorting the data or misleading viewers.
• Clarity : Graphical methods should be clear and easy to read. Graphs should be designed with the viewer in mind, using appropriate colors, labels, and titles to ensure that the message of the graph is conveyed effectively.

Advantages of Graphical Methods

Graphical methods offer several advantages for analyzing and presenting data, including:

• Clear visualization: Graphical methods provide a clear and intuitive visual representation of data that can help people understand complex relationships, trends, and patterns in the data. This can be particularly useful when dealing with large and complex data sets.
• Efficient communication: Graphical methods can help to communicate complex data sets in an efficient and accessible way. Visual representations can be easier to understand than numerical data alone, and can help to convey key messages quickly.
• Effective comparison: Graphical methods allow for easy comparison between different data sets, making it easier to identify trends, patterns, and differences. This can help in making decisions, identifying areas for improvement, or developing new insights.
• Improved decision-making: Graphical methods can help to inform decision-making by presenting data in a clear and easy-to-understand format. They can also help to identify key areas of focus, enabling individuals or teams to make more informed decisions.
• Increased engagement: Graphical methods can help to engage audiences by presenting data in an engaging and interactive way. This can be particularly useful in presentations or reports, where visual representations can help to maintain audience attention and interest.
• Better understanding: Graphical methods can help individuals to better understand the data they are working with, by providing a clear and intuitive visual representation of the data. This can lead to improved insights and decision-making, as well as better understanding of the implications of the data.

Limitations of Graphical Methods

Here are a few limitations to consider:

• Misleading representation: Graphical methods can potentially misrepresent data if they are not designed properly. For example, inappropriate scaling or labeling of the axes or the use of certain types of graphs can create a distorted view of the data.
• Limited scope: Graphical methods can only display a limited amount of data, which can make it difficult to capture the full complexity of a data set. Additionally, some types of data may be difficult to represent visually.
• Time-consuming : Creating graphs can be a time-consuming process, particularly if multiple graphs need to be created and analyzed. This can be a limitation in situations where time is limited or resources are scarce.
• Technical skills: Some graphical methods require technical skills to create and interpret. For example, certain types of graphs may require knowledge of specialized software or programming languages.
• Interpretation : Interpreting graphs can be subjective, and the same graph can be interpreted in different ways by different people. This can lead to confusion or disagreements when using graphs to communicate data.
• Accessibility : Some graphical methods may not be accessible to all audiences, particularly those with visual impairments. Additionally, some types of graphs may not be accessible to those with limited literacy or numeracy skills.

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Statistical Methods in Medical Research pp 27–31 Cite as

Graphic Presentation of Data

• Charan Singh Rayat 2  
• First Online: 24 August 2018

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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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Definition of graphic

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Definition of graphic  (Entry 2 of 3)

Definition of -graphic  (Entry 3 of 3)

• picturesque
• illustration

graphic , vivid , picturesque mean giving a clear visual impression in words.

graphic stresses the evoking of a clear lifelike picture.

vivid suggests an impressing on the mind of the vigorous aliveness of something.

picturesque suggests the presentation of a striking or effective picture composed of features notable for their distinctness and charm.

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Word History

Adjective and Noun

Latin graphicus , from Greek graphikos , from graphein

Adjective combining form

Late Latin -graphicus , from Greek -graphikos , from graphikos

1660, in the meaning defined at sense 3c

1889, in the meaning defined at sense 3b

Phrases Containing graphic

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Dictionary Entries Near graphic

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“Graphic.” Merriam-Webster.com Dictionary , Merriam-Webster, https://www.merriam-webster.com/dictionary/graphic. Accessed 19 Apr. 2024.

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Graphical representation of Data: Meaning & Importance

Contents in the Article

Graphical Representation 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.

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:

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.

Utility of Graphical Presentation

The diagram occupy an important place in statistical method, because

• They are attractive and impressive – Diagrams are attractive and create lasting impression. A person who does not like to devote even a single minute to the study of a page containing numerical tables, in most cases would not like to take his eyes away from an attractively constructed diagram even from the same data. They do not strain the mind of the observer. Besides being attractive, they have propaganda and publicity value. A common man who does not want to indulge in figures, gets message from a well prepared diagram.
• They make data simple and intelligible – Diagrams have the merit of rendering the whole data readily intelligible. The mass of complex data, when depicted through a diagram, an be understood easily. Diagrams bring forth the characteristics of data. For example, if a study is made of the expenditure pattern of two families with the help of figures it will not be very clear, but when figures are translated through the media diagram, the difference between their expenditure patterns will be at once clear.
• They make comparison possible – Diagrams make comparison between two sets of data possible. This is one of the objectives of a diagrammatic presentation. In absolute figures, the comparison is sometimes not very clear, but diagrammatic presentation makes it simpler and easier. For example, the data on prices may not be very clear to a common man, but when they are shown in a diagram, the rise or fall in the prices is visible at a glance.
• They save time and labour- Diagrammatic presentation saves a lot of time which could have been otherwise lost in grasping the significance of numerical data. Without straining one’s mind, the basic features of the data can be understood. The data which will take hours to understand them, their diagrammatic presentation will make their basic characteristics clear in minutes.
• They have universal utility- Diagrammatic presentation of statistical data is practiced universally. It is a widely used technique in economic, business, administration, social and other fields.
• They give more information- A diagram depicts more information than the data shown in a table. It clarifies the existing trend in the data and how the trend changes. Though such information is there in the tables also, but to find out trend from them is a difficult and a time-consuming job.

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What are Presentation Graphics?

Pre-requisites: Introduction to Computer Graphics

Graphics are defined as any sketch or a drawing or a special network that pictorially represents some meaningful information. Computer Graphics is used where a set of images needs to be manipulated or the creation of the image in the form of pixels and is drawn on the computer. Computer Graphics can be used in digital photography, film, entertainment, electronic gadgets, and all other core technologies which are required. It is a vast subject and area in the field of computer science. Computer Graphics can be used in UI design, rendering, geometric objects, animation, and many more. 

Presentation graphics provides predefined backgrounds and simple page layouts to help in the creation of slides. These slides can be moved automatically within seconds.

Slides: 

Slides mean we have text, graphics, audio clips, video clips, animations, and other effects   Presentation graphics is also known as Presentation Software. The best example of presentation graphics is Microsoft PowerPoint. 

In recent days we have a new presentation tool that is: our Web browser and that is for creating Web pages, like Microsoft’s FrontPage and Adobe’s PageMill. 

Rules to Design Presentation:

• Keep it simple: Make it simple to understand. It only contains information regarding your topic.
• Correct Spelling:   We have to be careful with the spelling that we have written.
• Consistency: There is need to be continuous flow from one slide to another.
• Don’t put too much on a Slide: Don’t write too much. just give a brief description and important points.
• Use Fonts Properly: Only you can use two font styles in the presentation.
• Find Your Equipment: First, you have to be confident with your topic and details about it.

Uses: 

Presentation graphics programs are mainly concerned with the display of graphs and charts but now allow users to attach anything from text to animations. When Compared to other programs like Excel, PowerPoint follows a slideshow format.

Applications:  

In the following areas we can use presentation software:

• Google Slides
• Microsoft Office
• WPS Office 
• Photo Slideshow with Music

Advantages:

• Less Cost: The cost is low to use presentation software
• Logical Ideas: Tables and graphs are used to represent information then a logical order is created to give a clear idea for viewers.
• Acceptability: By using this busy person can easily get an idea about the topic.

Disadvantages:

• Time-taking process. It needs more time to prepare.
• Data can sometimes be lost.
• Errors and Mistakes can occur during design.

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Table of Contents

Presentation definition & meaning, what is a presentation, 10 types of presentations, presentation uses, purpose, importance, what’s in a presentation parts, how to design a presentation, presentation vs. deck, what’s the difference between a presentation, representation, & speech, presentation sizes, presentation ideas & examples, graphic design, presentation.

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