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Data Handling Class 8 PPT

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Unit 4: Data handling

Looking for information (recap).

• Reading pictographs (Opens a modal)
• Reading bar charts: comparing two sets of data (Opens a modal)
• Read picture graphs (multi-step problems) Get 3 of 4 questions to level up!
• Read bar graphs (2-step problems) Get 3 of 4 questions to level up!

Organising data

• No videos or articles available in this lesson
• Knowing frequency distribution table better Get 3 of 4 questions to level up!
• Constructing frequency table Get 3 of 4 questions to level up!
• Interpreting a histogram (Opens a modal)
• Creating a histogram (Opens a modal)
• Read histograms Get 3 of 4 questions to level up!
• Create histograms Get 3 of 4 questions to level up!
• Reading pie graphs (circle graphs) (Opens a modal)
• Plotting pie charts Get 3 of 4 questions to level up!

Data Handling

Data handling is considered one of the most important topics in statistics as it deals with collecting sets of data, maintaining security, and the preservation of the research data. The data here is a set of numbers that help in analyzing that particular set or sets of data. Data handling can be represented visually in the form of graphs. Let us learn more about this interesting concept, the different graphs used, and solve a few examples for better understanding.

Definition of Data Handling

Data Handling is the process of gathering, recording, and presenting information in a way that is helpful to analyze, make predictions and choices. Anything that can be grouped based on certain comparable parameters can be thought of as data . Parameters mean the context in which the comparison is made between the objects. Data handling usually represent in the form of pictographs, bar graphs, pie charts, histograms , line graphs, stem and leaf plots , etc. All of them have a different purpose to serve. Have a look at the composition of the air that we have learned about in our science classes.

The constituents of air are presented with different colors in the form of parts of a pie. Do you think, a bar chart, line graph, or any other graphical representation would be able to communicate the information as effectively as this one. Definitely no. With a detailed study of each of them, you can clearly understand the purpose of each of them and use them suitably.

Types of Data

Data handling is performed depending on the types of data. Data is classified into two types, such as Quantitative Data and Qualitative Data. Quantitive data gives numerical information, while qualitative data gives descriptive information about anything. Quantitative can be either discrete or continuous data.

Important Terms in Data Handling

In data handling, there are 4 important terms or most frequently used terms that make it simple to understand the concept better. The terms are:

• Data: It is the collection of numerical figures of any kind of information
• Raw Data: The observation gathered initially is called the raw data.
• Range: It is the difference between the highest and lowest values in the data collection.
• Statistics : It deals with the collection, representation, analysis, and interpretation of numerical data.

Steps Involved in Data Handling

Following are the steps to follow in data handling:

Graphical Representation of Data Handling

Data handling can be represented in a number of graphical ways. Here is a list of various types of graphical representations of data that are very effective in data handling.

Bar graphs represent data in the form of vertical or horizontal bars showing data with rectangular bars and the heights of bars are proportional to the values that they represent. Bar graphs help in the comparison of data and this type of graph is most widely used in statistics. Look at the image below as an example.

Pictographs or Picture Graphs

Pictograph is a type of graph where information is represented in the form of pictures, icons, or symbols. It is the simplest form of representing data in statistics and data handling. Since the use of images and symbols are more in a pictograph, interpreting data is made easy along with representing a large number of data. Look at the example below for a better understanding.

Line Graphs

In data handling the data represented in the form of a line on a graph is the line graph . The graph helps in showcasing the different trends or changes in the data. The line segment plotted on the graph is constructed by connecting individual data points together. Look at the example below to understand it better.

A pie chart is data represented in a circular graph divided into smaller sectors to denote certain information. Pie charts help in showcasing the profit and loss for a business, while in school in showcasing the number depending on the data. This kind of chart is widely used in marketing sales. Look at the example below, the pie chart shows how people like the mentioned fruits from a group of 360.

Scatter Plot

Scatter plot represents the points and then the best fit line is drawn through some of the points. Any 3D data in data handling can be represented by a scatter plot. Look at the example below to understand it better.

Related Topic

Listed below are a few interesting topics related to data handling. Take a look.

• Absolute Value Graph
• Frequency Distribution Table
• Probability and Statistics

Examples on Data Handling

Example 1: Henry wants to introduce his 5-year-old daughter to data handling. Which type of graphical representation can he use for this?

As his daughter is just 5 years old, he should prefer using Pictograph to introduce data handling. In this representation, simple pictures like circles, stars are drawn to represent different data.

Example 2: How is data represented graphically?

Solution: Various types of graphs that can be used for representing data are:

• Scatter plot
• Pie chart/ Circle chart
• Picture graph

Depending on the purpose, a suitable graph can be chosen.

Example 3: Here is a review of an electronic product. Out of all the people who gave their reviews, 16 of them gave a 5-star rating to the product. Can you find out how many people provided their feedback in all?

Let the total reviews be x.

Number of people who gave 5 star = 16

Percentage of people who gave 5 star = 64%

So, number of people who gave 5 star = 64 % × x

16 = 64/100 × x

x = (16 × 64)/100

Therefore, 25 people gave reviews for the product

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Practice Questions on Data Handling

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FAQs on Data Handling

What is data handling.

Data Handling is the process of gathering, recording, and presenting information in a way that is helpful to analyze, make predictions and choices. There are two types of data handling namely quantitative data and qualitative data. Data handling can be represented through various graphs.

What are the Two Types of Data Handling?

The two types of data handling are qualitative data and quantitative data. Quantitive data gives numerical information, while qualitative data gives descriptive information about anything. Quantitative can be either discrete or continuous data.

What are the Steps Involved in Data Handling?

The six steps that are involved in data handling are:

• Collection of Data
• Presentation of Data
• Graphical Representation of Data
• Analyzing the Data

What are the Types of Graphical Representations in Data Handling?

There are numerous types of graphical representation for the data that are available. Some of the most extensively used graphical representations are :

What is the Difference Between Data and Information in Data Handling?

The term data refers to the collection of certain facts that are quantitive in nature like height, number of children, etc. Information on the other hand is a form of data after being processed, arranged, and presented in a form that gives meaning to the data.

What is the Difference Between the Chart and Graph?

The difference between chart and graph can be understood from the fact that - All graphs are charts but every chart is not a graph. Charts display data in the form of a diagram, table, or graph. So, the graph is just a pictorial way of presentation of information.

Data Handling Class 8 Maths Formula

Data Handling Formula: Data Handling involves the systematic gathering, recording, and presentation of information in a manner that facilitates analysis, predictions, and decision-making. Essentially, any elements that can be grouped according to specific comparable attributes can be considered as data.

September 10, 2023

Table of Contents

Data Handling Class 8 Maths Formula holds significant importance within statistics, encompassing tasks such as data collection, ensuring data security, and the maintenance of research data integrity. It involves working with sets of numbers that facilitate the analysis of specific data sets. Visual representation is a fundamental aspect of data handling, often manifested through various types of graphs. Delving into this intriguing concept, we explore diverse graph forms and engage in solving illustrative examples to enhance comprehension.

Definition of Data Handling

Data Handling involves the systematic gathering, recording, and presentation of information in a manner that facilitates analysis, predictions, and decision-making. Essentially, any elements that can be grouped according to specific comparable attributes can be considered as data. These attributes are the context in which the objects are compared. The representation of data handling typically takes the form of diverse graphical formats such as pictographs, bar graphs, pie charts, histograms, line graphs, and stem and leaf plots, among others. Each of these graphical forms serves a distinct purpose.

For instance, consider the illustration of the composition of air, which we have encountered in our science lessons. The components of air are depicted using different colors, resembling parts of a pie. This visualization effectively conveys information that would not be as comprehensible through a bar chart, line graph, or any other graphical representation. By closely studying each of these graphical methods, you can grasp their individual purposes and employ them suitably for various scenarios.

Also Check – Rational Number Formula

Types of Data

Data handling strategies vary according to the types of data being dealt with. Data is categorized into two fundamental types: Quantitative Data and Qualitative Data. Quantitative data entails numerical information, while qualitative data provides descriptive insights. Quantitative data is further sub-divides into discrete and continuous data.

Also Check – Quadrilaterals Formula

Important Terms in Data Handling

Within the realm of data handling, there exist four pivotal terms that play a significant role in enhancing the comprehension of the concept. These terms are as follows:

Data: This encompasses a compilation of numerical values, constituting various forms of information.

Download PDF Data Handling Class 8 Maths Formula

Raw Data: The initial observations gathered form what is referred to as raw data, representing the fundamental building blocks of information.

Range: This denotes the distinction between the highest and lowest values within the assortment of data, encapsulating the span of values.

Statistics: The domain of statistics revolves around the tasks of assembling, illustrating, scrutinizing, and interpreting numerical data, facilitating the extraction of meaningful insights

Also Check – Linear Equation Formula

Steps Involved in Data Handling

Graphical representation of data handling.

Data manipulation can be portrayed through diverse graphical methods. The following list encompasses various types of graphical representations that are highly efficient in facilitating data handling.

Bar graphs visually depict data using vertical or horizontal bars, wherein the lengths of these bars are proportional to the corresponding values they represent. This graphical format proves invaluable in facilitating data comparison, making it one of the most extensively utilized types of graphs in the realm of statistics. Refer to the image below for an illustrative example of a bar graph within the context of data handling.

Pictographs or Picture Graphs

A pictograph is a graphical representation wherein data is conveyed through the utilization of pictures, icons, or symbols. It constitutes the most elementary method of illustrating data within the realms of statistics and data management. Given the prevalence of images and symbols in a pictograph, data interpretation becomes notably straightforward, further facilitating the depiction of substantial volumes of data. The example provided below offers enhanced clarity in comprehending this concept.

Line Graphs

In the realm of data manipulation, when information is depicted using a visual representation resembling a line on a graph, it is referred to as a line graph. This graphical tool is valuable for illustrating various shifts or fluctuations within the data. The line that appears on the graph is formed by connecting individual data points, thereby creating line segments. To gain a clearer comprehension, refer to the provided example.

A pie chart entails data visualized within a circular graph partitioned into smaller segments, each signifying specific information. Such charts are useful for displaying business financials like profits and losses, as well as educational data like quantities. This graphical representation is extensively employed in the realms of marketing and sales. For instance, consider the example provided below, where a pie chart illustrates preferences for various fruits among a total of 360 individuals.

Scatter Plot

A scatter plot portrays individual data points, often accompanied by a best-fit line drawn through a subset of these points. This type of graph is capable of depicting three-dimensional data in the context of data analysis. To enhance your comprehension, refer to the provided example below.

Data Handling Class 8 Maths Formula FAQs

Data handling encompasses the activities of collecting, recording, and presenting information in a manner conducive to analysis, prediction, and decision-making. It involves two primary categories: quantitative data and qualitative data. The visualization of data handling can be accomplished through diverse types of graphs.

There are two classifications in data handling: qualitative data and quantitative data. Quantitative data provides numerical information, whereas qualitative data offers descriptive insights. Quantitative data can be further categorized as either discrete or continuous data.

The six steps that are involved in data handling are: Purpose Collection of Data Presentation of Data Graphical Representation of Data Analyzing the Data Conclusion

Distinguishing between a chart and a graph becomes evident when considering that while all graphs fall under the category of charts, not all charts qualify as graphs. Charts encompass various methods of data representation such as diagrams and tables. In contrast, a graph specifically denotes a visual representation of information, presenting it pictorially.

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• RD Sharma Solutions
• Chapter 23 Classification And Tabulation Of Data

RD Sharma Solutions for Class 8 Maths Chapter 23 Data Handling - I (Classification and Tabulation of Data)

The word data means information. Collection of observations is the first step in statistical investigations. Once the data is collected, it needs to be presented in a tabular form. All these salient features shall be discussed in this chapter. Students who aim to secure top scores in their examinations can refer to RD Sharma Class 8, which is the best reference material developed by our subject experts keeping in mind the latest syllabus. Students are advised to practise on a regular basis which will benefit them in their exams. The PDF of RD Sharma Class 8 consisting of solutions from this chapter can be downloaded easily from the links given below.

Chapter 23 Data Handling – I (Classification and Tabulation of Data) contains two exercises and the RD Sharma Class 8 Solutions present in this page provide solutions to the questions present in each exercise. Now, let us have a look at the concepts discussed in this chapter.

• Presentation of data.
• Discrete frequency distribution.
• Continuous or grouped frequency distribution.
• Construction of a discrete frequency distribution.
• Construction of a grouped frequency distribution.
• RD Sharma Solutions for Class 8 Maths Chapter 1 Rational Numbers
• RD Sharma Solutions for Class 8 Maths Chapter 2 Powers
• RD Sharma Solutions for Class 8 Maths Chapter 3 Squares and Square Roots
• RD Sharma Solutions for Class 8 Maths Chapter 4 Cubes and Cube Roots
• RD Sharma Solutions for Class 8 Maths Chapter 5 Playing with Numbers
• RD Sharma Solutions for Class 8 Maths Chapter 6 Algebraic Expressions and Identities
• RD Sharma Solutions for Class 8 Maths Chapter 7 Factorization
• RD Sharma Solutions for Class 8 Maths Chapter 8 Division of Algebraic Expressions
• RD Sharma Solutions for Class 8 Maths Chapter 9 Linear Equations in One Variable
• RD Sharma Solutions for Class 8 Maths Chapter 10 Direct and Inverse Variations
• RD Sharma Solutions for Class 8 Maths Chapter 11 Time and Work
• RD Sharma Solutions for Class 8 Maths Chapter 12 Percentage
• RD Sharma Solutions for Class 8 Maths Chapter 13 Profit, Loss, Discount and Value Added Tax (VAT)
• RD Sharma Solutions for Class 8 Maths Chapter 14 Compound Interest
• RD Sharma Solutions for Class 8 Maths Chapter 15 Understanding Shapes – I (Polygons)
• RD Sharma Solutions for Class 8 Maths Chapter 16 Understanding Shapes – II (Quadrilaterals)
• RD Sharma Solutions for Class 8 Maths Chapter 17 Understanding Shapes – II (Special Types of Quadrilaterals)
• RD Sharma Solutions for Class 8 Maths Chapter 18 Practical Geometry (Constructions)
• RD Sharma Solutions for Class 8 Maths Chapter 19 Visualising Shapes
• RD Sharma Solutions for Class 8 Maths Chapter 20 Mensuration – I (Area of a Trapezium and a Polygon)
• RD Sharma Solutions for Class 8 Maths Chapter 21 Mensuration – II (Volumes and Surface Areas of a Cuboid and a Cube)
• RD Sharma Solutions for Class 8 Maths Chapter 22 Mensuration – III (Surface Area and Volume of a Right Circular Cylinder)

RD Sharma Solutions for Class 8 Maths Chapter 23 Data Handling – I (Classification and Tabulation of Data)

• RD Sharma Solutions for Class 8 Maths Chapter 24 Data Handling – II (Graphical Representation of Data as Histograms)
• RD Sharma Solutions for Class 8 Maths Chapter 25 Data Handling – III (Pictorial Representation of Data as Pie Charts)
• RD Sharma Solutions for Class 8 Maths Chapter 26 Data Handling – IV (Probability)
• RD Sharma Solutions for Class 8 Maths Chapter 27 Introduction to Graphs
• Exercise 23.1 Chapter 23 Data Handling – I (Classification and Tabulation of Data)
• Exercise 23.2 Chapter 23 Data Handling – I (Classification and Tabulation of Data)

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Access answers to Maths RD Sharma Solutions For Class 8 Chapter 23 Data Handling – I (Classification and Tabulation of Data)

EXERCISE 23.1 PAGE NO: 23.7

1. Define the following terms : (i) Observations (ii) Raw data (iii) Frequency of an observation (iv) Frequency distribution (v) Discrete frequency distribution (vi) Grouped frequency distribution (vii) Class-interval (viii) Class-size (ix) Class limits (x) True class limits

(i) Observations:

Observation is the value at a particular period of a particular variable.

(ii) Raw data:

Raw data is the data collected in its original form.

(iii) Frequency of an observation:

Frequency of an observation is the number of times a certain value or a class of values occurs.

(iv) Frequency distribution:

Frequency distribution is the organization of raw data in table form with classes and frequencies.

(v) Discrete frequency distribution:

Discrete frequency distribution is a frequency distribution where sufficiently great numbers are grouped into one class.

(vi) Grouped frequency distribution:

Grouped frequency distribution is a frequency distribution where several numbers are grouped into one class.

(vii) Class-interval:

Class interval is a group under which large number of data is grouped to analyse its Range and Distribution.

(viii) Class-size:

Class size is the difference between the upper and the lower values of a class.

(ix) Class limits:

Class limits are the smallest and the largest observations (data, events, etc.) in a class.

(x) True class limits:

True class limits are the actual class limits of a class.

2. The final marks in mathematics of 30 students are as follows: 53, 61, 48, 60, 78, 68, 55, 100, 67, 90, 75, 88, 77, 37, 84, 58, 60, 48, 62, 56, 44, 58, 52, 64, 98, 59, 70, 39, 50, 60 (i) Arrange these marks in the ascending order, 30 to 39 one group, 40 to 49 second group etc. Now answer the following: (ii) What is the highest score? (iii) What is the lowest score? (iv) What is the range? (v) If 40 is the pass mark how many have failed? (vi) How many have scored 75 or more? (vii) Which observations between 50 and 60 have not actually appeared? (viii) How many have scored less than 50?

The given raw data can be arranged in an ascending order.

The class intervals are 30 – 39, 40 – 49, …, 100 – 109.

Then, take the raw data and place it in the appropriate class intervals.

(i)   The marks can be arranged in an ascending order as shown below:

(ii)  The Highest score is 100.

(iii)  The Lowest score is 37.

(iv) The Range is 100 – 37 i.e., 63.

(v)  If 40 is the passing mark, then the number of students who failed is 2 (i.e. 37, 39).

(vi)  The number of students scoring 75 and above is 8 (i.e. 75, 77, 78, 84, 88, 90, 98, 100).

(vii)  The marks 51, 54, and 57 do not actually appear between 50 and 60.

(viii)  The number of students scoring less than 50 is 5 (i.e. 37, 39, 44, 48, 48).

3. The weights of new born babies (in kg) in a hospital on a particular day are as follows: 2.3, 2.2, 2.1, 2.7, 2.6, 3.0, 2.5, 2.9, 2.8, 3.1, 2.5, 2.8, 2.7, 2.9, 2.4 (i) Rearrange the weights in descending order. (ii) Determine the highest weight. (iii) Determine the lowest weight. (iv) Determine the range. (v) How many babies were born on that day? (vi) How many babies weigh below 2.5 kg? (vii) How many babies weigh more than 2.8 kg? (viii) How many babies weigh 2.8 kg?

(i) The weights of the newly born babies in descending order are as follows: 3.1, 3.0, 2.9, 2.9, 2.8, 2.8, 2.7, 2.7, 2.6, 2.5, 2.4, 2.4, 2.3, 2.2, 2.1

(ii) The highest weight is 3.1 kg

(iii) The lowest weight is 2.1 kg

(iv) The range is 3.1-2.1, i.e. 1 kg

(v) The number of babies born on that day is 15

(vi) The number of babies whose weights are below 2.5 kg is 4 (i.e. 2.4, 2.3, 2.2, 2.1)

(vii) The number of babies whose weights are more than 2.8 kg is 4 (i.e. 3.1, 3.0, 2.9, 2.9)

(viii) The number of babies whose weight is 2.8 kg is 2.

4. Following data gives the number of children in 41 families : 1, 2, 6, 5, 1, 5, 1, 3, 2, 6, 2, 3, 4, 2, 0, 0, 4, 4, 3, 2, 2, 0, 0, 1, 2, 2, 4, 3, 2, 1, 0, 5, 1, 2, 4, 3, 4, 1, 6, 2, 2. Represent it in the form of a frequency distribution.

The data can be put in the form of frequency distribution in the following manner:

5. Prepare a frequency table of the following scores obtained by 50 students in a test: 42, 51, 21, 42, 37, 37, 42, 49, 38, 52, 7, 33, 17,44, 39, 7, 14, 27, 39, 42, 42, 62, 37, 39, 67, 51,53, 53, 59, 41, 29, 38, 27, 31, 54, 19, 53, 51, 22,61, 42, 39, 59, 47, 33, 34, 16, 37, 57, 43

Solution: The frequency table of 50 students is given below:

6. A die was thrown 25 times and following scores were obtained : 1, 5, 2, 4, 3, 6, 1, 4, 2, 5, 1, 6, 2, 6, 3, 5, 4, 1, 3, 2, 3, 6, 1, 5, 2 Prepare a frequency table of the scores.

The frequency of the scores of the die is shown below:

7. In a study of number of accidents per day, the observations for 30 days were obtained as follows : 6, 3, 5, 6, 4, 3, 2, 5, 4, 2, 4, 2, 1, 2, 2, 0, 5, 4, 6, 1, 6, 0, 5, 3, 6, 1, 5, 5, 2, 6 Prepare a frequency distribution table.

Given that,

6, 3, 5, 6, 4, 3, 2, 5, 4, 2, 4, 2, 1, 2, 2,

0, 5, 4, 6, 1, 6, 0, 5, 3, 6, 1, 5, 5, 2, 6

From the above set we can observe that 0 occurs for 2 times,1 occurs for 3times, 2 occurs for 6times, 3 occurs for 3times, 4 occurs for 4times, 5 occurs for 6times, 6 occurs for 6 times.

The frequency table for the number of accidents per day for a period of 30 days is shown below:

8. Prepare a frequency table of the following ages (in years) of 30 students of class VIII in your school :

13, 14, 13, 12, 14, 13, 14, 15, 13, 14, 13, 14, 16, 12, 14, 13, 14, 15, 16, 13, 14, 13, 12, 17, 13, 12, 13, 13, 13, 14

The frequency table of the ages of 30 students of class VII in the school is shown below:

9. Following figures relate to the weekly wages (in Rs.) of 15 workers in a factory: 300, 250, 200, 250, 200, 150, 350, 200, 250, 200, 150, 300, 150, 200, 250 Prepare a frequency table. (i) What is the range in wages (in Rs)? (ii) How many workers are getting Rs. 350? (iii) How many workers are getting the minimum wages?

The frequency table shows the weekly wages of 15 workers in a factory:

(i) The range of wages (in Rs) is 350-150 i.e. 200.

(ii) From the frequency table, we can see that the number of workers earning Rs 350 is 1.

(iii) Here, the minimum wage is 150. Hence, the number of workers earning the minimum wage is 3.

10. Construct a frequency distribution table for the following marks obtained by 25 students in a history test in class VIII of a school : 9, 7, 12, 20, 9, 18, 25, 17, 19, 9, 12, 9, 12, 18, 17, 19, 20, 25, 9, 12, 17, 19, 19, 20, 9 (i) What is the range of marks? (ii) What is the highest mark? (iii) Which mark is occurring more frequently?

The frequency distribution table is given below:

(i) The range of marks is 25-9, i.e. 16.

(ii) The highest mark is 25.

(iii) The mark that occurs most frequently is 9. It occurs 6 times.

EXERCISE 23.2 PAGE NO: 23.14

1. The marks obtained by 40 students of class VIII in an examination are given below : 16, 17, 18, 3, 7, 23, 18, 13, 10, 21, 7, 1, 13, 21, 13, 15, 19, 24, 16, 3, 23, 5, 12, 18, 8, 12, 6, 8, 16, 5, 3, 5, 0, 7, 9, 12, 20, 10, 2, 23. Divide the data into five groups namely 0-5, 5-10, 10-15, 15-20 and 20-25 and prepare a grouped frequency table.

The frequency table for the marks of 40 students of class VIII in an examination is shown below:

2. The marks scored by 20 students in a test are given below: 54, 42, 68, 56, 62, 71, 78, 51, 72, 53, 44, 58, 47, 64, 41, 57, 89, 53, 84, 57. Complete the following frequency table:

What is the class interval in which the greatest frequency occurs?

The frequency table can be completed as follows:

The class interval with the greatest frequency (8) is 50-60.

3. The following is the distribution of weights (in kg) of 52 persons:

(i) What is the lower limit of class 50-60? (ii) Find the class marks of the classes 40-50, 50-60. (iii) What is the class size?

(i) The lower limit of the class 50-60 is 50.

(ii) Class mark for the class 40-50:

i.e., (40+50) / 2 = 90/2 = 45

Again, Class mark for the class 50-60:

i.e., (50+60) / 2 = 110/2 = 55

(iii) Here the class size is 40-30, i.e. 10.

4. Construct a frequency table for the following weights (in gm) of 35 mangoes using the equal class intervals, one of them is 40-45 (45 not included) : 30, 40, 45, 32, 43, 50, 55, 62, 70, 70, 61, 62, 53, 52, 50, 42, 35, 37, 53, 55, 65, 70, 73, 74, 45, 46, 58, 59, 60, 62, 74, 34, 35, 70, 68. (i) What is the class mark of the class interval 40-45? (ii) What is the range of the above weights? (iii) How many classes are there?

(i) Class mark for the class interval 40 – 45:

Class mark = (40+45) / 2 = 85/2 = 42.5

(ii) Range of the above weights:

Range = Highest value – Lowest value

Range = 74 – 30 = 44

(iii) Number of classes = 9

5. Construct a frequency table with class-intervals 0-5 (5 not included) of the following marks obtained by a group of 30 students in an examination : 0, 5, 7, 10, 12, 15, 20, 22, 25, 27, 8, 11, 17, 3, 6, 9, 17, 19, 21, 29, 31, 35, 37, 40, 42, 45, 49, 4, 50, 16.

The frequency table with class intervals 0 – 5, 5 – 10, 10 – 15, . . . , 45 – 50 is shown below:

6. The marks scored by 40 students of class VIII in mathematics are given below : 81, 55, 68, 79, 85, 43, 29, 68, 54, 73, 47, 35, 72, 64, 95, 44, 50, 77, 64, 35, 79, 52, 45, 54, 70, 83, 62, 64, 72, 92, 84, 76, 63, 43, 54, 38, 73, 68, 52, 54. Prepare a frequency distribution with class size of 10 marks.

The frequency table of the marks scored by 40 students of class VIII in mathematics is shown below:

7. The heights (in cm) of 30 students of class VIII are given below : 155, 158, 154, 158, 160, 148, 149, 150, 153, 159, 161, 148, 157, 153, 157, 162, 159, 151, 154, 156, 152, 156, 160, 152, 147, 155, 163, 155, 157, 153. Prepare a frequency distribution table with 160-164 as one of the class intervals.

The frequency distribution table is shown below:

8. The monthly wages of 30 workers in a factory are given below:

830, 835, 890, 810, 835, 836, 869, 845, 898, 890, 820, 860, 832, 833, 855, 845, 804, 808, 812, 840, 885, 835, 836, 878, 840, 868, 890, 806, 840, 890. Represent the data in the form of a frequency distribution with class size 10.

The frequency table of the monthly wages of 30 workers in a factory is shown below:

9. Construct a frequency table with equal class intervals from the following data on the monthly wages (in rupees) of 28 labourers working in a factory, taking one of the class intervals as 210-230 (230 not included) : 220, 268, 258, 242, 210, 268, 272, 242, 311, 290, 300, 320, 319, 304, 302, 318, 306, 292, 254, 278, 210, 240, 280, 316, 306, 215, 256, 236.

The frequency table of the monthly wages of 28 laborers working in a factory is shown below:

10. The daily minimum temperatures in degrees Celsius recorded in a certain Arctic region are as follows : – 12.5, -10.8, -18.6, -8.4, -10.8, -4.2, -4.8, -6.7, -13.2, -11.8, -2.3, 1.2, 2.6, 0, -2.4, 0, 3.2, 2.7, 3.4, 0, -2.4, -2.4, 0, 3.2, 2.7, 3.4, 0, -2.4, -5.8, -8.9, -14.6, -12.3, -11.5, -7.8, -2.9 Represent them as frequency distribution table taking -19.9 to -15 as the first class interval.

The frequency table of the daily minimum temperatures is shown below:

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