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RS Aggarwal Solutions

RS Aggarwal Solutions Class 8 Chapter-21 Data Handling (Ex 21A) Exercise 21.1

RS Aggarwal Solutions Class 8 Chapter-21 Data Handling (Ex 21A) Exercise 21.1

Q: 3. Why is it crucial to correctly determine the 'range' of the data before creating class intervals in Exercise 21A?

Determining the range (the difference between the highest and lowest observation) is a critical first step because it helps you decide the span of your data. This information is essential for choosing a logical class size and the number of class intervals. An incorrect range can lead to class intervals that are too broad or too narrow, making the final frequency table less effective at showing patterns in the data.

Q: 6. What is the specific role of 'tally marks' in the solutions for Data Handling Exercise 21A?

Tally marks serve as a systematic and real-time counting tool. When dealing with a list of observations, it is very easy to lose track or double-count. Tally marks provide a foolproof method to record each observation as you encounter it. The practice of grouping them in sets of five (four vertical lines and one diagonal slash) makes the final counting of the frequency for each class interval quicker and less prone to errors.

RS Aggarwal Solutions Class 8 Chapter-21 Data Handling (Ex 21A) Exercise 21.1 - Free PDF

Free PDF download of RS Aggarwal Solutions Class 8 Chapter-21 Data Handling (Ex 21A) Exercise 21.1 solved by Expert Mathematics Teachers on Vedantu.com. All Exercise 21.1 Questions with Solutions for Class 8 RS Aggarwal to help you to revise the complete syllabus and score more marks. Register for online coaching for IIT JEE (Mains & Advanced) and other engineering entrance Exams. You can also register Online for Class 8 Science tuition on Vedantu.com to score more marks in your Examination.

The presentation of data is critical in order for it to be easily understood. This Chapter primarily describes the steps involved in preparing the frequency distribution table for the given data. The solutions are designed to securely and safely Exercise by Exercise based on the students' grasping ability.

These solutions are explained in simple terms to assist students in passing the Exam. PDF is designed to allow users to download solutions either Exercise-by-Exercise or Chapter-by-Chapter based on their needs. Students can use the RS Aggarwal Solutions for Class 6 Chapter 21 Data Handling – I (Data Presentation) PDF that is provided here.

In statistics, "Data Handling" is an important concept that ensures the integrity of research data by addressing issues such as security, confidentiality, and research data preservation. We have information in the form of a numerical figure in every field. Every figure of this type is referred to as an observation. In general, data is the collection of all observations. Statisticians use a variety of Data Management methods to manage their data. Let us discuss what Data Handling is and the various methods for handling data in this article.

About Data Handling

Data Handling entails gathering a set of data and presenting it in a different format. Data is a set of numerical figures that represent a specific type of information. The raw data is the collection of observations that are initially gathered. Data can take any form. It could be in the form of words, numbers, measurements, descriptions, or observations. Data Handling is the process of ensuring that research data is collected, archived, or disposed of in a secure and safe manner during and after the analysis process.

Data Varieties

Data Handling methods can be used depending on the type of data. The information is divided into two categories:

Qualitative Information

Quantitative Information

Qualitative data describes something, whereas quantitative data provides numerical information about something. The quantitative data is further subdivided in this section. There are two types of data: discrete data and continuous data. Discrete data can only take specific values, such as whole numbers. The continuous data can have a value that falls within the specified range.

Steps for Data Handling

The following are the steps involved in the data handling process:

Step 1: Identifying the Issue

The purpose or problem statement must be identified and well defined during the Data Handling process.

Step 2: Gathering Data

Data pertinent to the problem statement is gathered.

Step 3: Presenting the Data

The collected data should be presented in a meaningful and understandable manner. It is possible to accomplish this by arranging the collected data in tally marks, table forms, and so on.

4th Step: Graphic Representation

Because the visual or graphical representation of data facilitates analysis and comprehension, presented data can be plotted in graphs, charts such as bar graphs, pie charts, and so on.

5th Step: Data Analysis

The data should be analyzed so that the necessary information can be derived from the data, allowing for subsequent actions to be taken.

Step 6: Finally,

We can deduce the solution to our problem statement from the data analysis.

How Should Data Be Represented?

Typically, data can be represented in one of the following ways. They are as follows:

Line Graphs and Bar Graphs
Pictographs
Histograms
Dot Plots for Stem and Leaf
Distribution of Frequency
Tables and graphs with totals

Now, we'll look at one of the methods for representing data using a "Bar Graph."

Bar Graph

Data can be represented in a variety of ways, including numbers, pictures, tables, graphics, and so on. Bar graphs are the most common type of graphical representation of data. A bar graph or bar chart depicts a visual interpretation of data using vertical or horizontal rectangular bars of equal width that are uniformly spaced concerning straightforward one another, with the lengths of the bars proportional to the data to be represented.

Vedantu is a platform that provides free CBSE Solutions (NCERT) and other study materials for students. Maths Students who are looking for better solutions can download Class 8 Maths NCERT Solutions to help you to revise the complete syllabus and score more marks in your Examinations.

FAQs on RS Aggarwal Solutions Class 8 Chapter-21 Data Handling (Ex 21A) Exercise 21.1

1. What key skills will I master by using the RS Aggarwal Solutions for Class 8 Maths Chapter 21, Exercise 21A?

By following the step-by-step solutions for Exercise 21A, you will master the fundamental skill of organising raw data. You will learn the correct procedure to construct a frequency distribution table, which includes determining the range, creating appropriate class intervals, using tally marks accurately, and recording the frequency for each class. This is a foundational skill for all further topics in data handling.

2. What is the correct method to construct a frequency distribution table for the questions in Exercise 21A?

The correct method, as demonstrated in the solutions, involves a few key steps:

First, identify the highest and lowest values in the given dataset to find the range.
Next, decide on a suitable number of class intervals (or groups) that cover the entire range of data. Ensure the classes do not overlap.
Go through the dataset and assign a tally mark for each data point in its corresponding class interval.
Finally, count the tally marks for each class to find the frequency and record it in the table.

3. Why is it crucial to correctly determine the 'range' of the data before creating class intervals in Exercise 21A?

Determining the range (the difference between the highest and lowest observation) is a critical first step because it helps you decide the span of your data. This information is essential for choosing a logical class size and the number of class intervals. An incorrect range can lead to class intervals that are too broad or too narrow, making the final frequency table less effective at showing patterns in the data.

4. What are some common mistakes to avoid when solving problems from RS Aggarwal Class 8 Chapter 21, Exercise 21A?

When working on Exercise 21A, students should be careful to avoid these common errors:

Incorrect Tally Counting: Miscounting or misplacing tally marks, especially with larger datasets.
Overlapping Class Intervals: For example, using intervals like 10-20 and 20-30. A value of 20 would fit in both, which is incorrect. Use non-overlapping intervals like 10-19 and 20-29 or exclusive intervals like 10-20 and 20-30 where the upper limit is excluded.
Forgetting a Data Point: Accidentally skipping a number while tabulating it.
Calculation Errors: Making simple mistakes while finding the range or counting frequencies.

5. How does creating a frequency distribution table in Ex 21A make raw data more understandable?

A frequency distribution table transforms a chaotic list of raw numbers into a structured and meaningful summary. Instead of looking at dozens of individual figures, the table groups the data into classes and shows how many data points fall into each group. This immediately helps in understanding the data's distribution, identifying which values occur most or least often, and spotting patterns that are impossible to see in the unorganised raw data.

6. What is the specific role of 'tally marks' in the solutions for Data Handling Exercise 21A?

Tally marks serve as a systematic and real-time counting tool. When dealing with a list of observations, it is very easy to lose track or double-count. Tally marks provide a foolproof method to record each observation as you encounter it. The practice of grouping them in sets of five (four vertical lines and one diagonal slash) makes the final counting of the frequency for each class interval quicker and less prone to errors.

7. Are the problem-solving methods in these RS Aggarwal solutions aligned with the CBSE 2025-26 syllabus?

Yes, the methods for data organisation and construction of frequency distribution tables provided in the solutions for RS Aggarwal Class 8 Chapter 21 are fully compliant with the latest CBSE curriculum guidelines for the 2025-26 academic year. Following these solutions ensures that you are preparing with the correct methodology expected in your school examinations.