Grouping data: Overview, Questions, Preparation

This chapter has multiple topics listed below:

Statistics Standard Deviation Correlation Bar Graph Chi Square Test Measures of Central Tendency Variance Extrapolation Null Hypothesis Pareto Chart Harmonic Mean How to find Median Statistics Definition Data Collection Methods Frequency Polygons Central Tendency Confidence Interval Data Handling Statistical Inference Quota Sampling Interquartile Range Quartiles Variance and Standard deviation Cluster Analysis Correlation and Regression Graphical Representation Least Square Method Level of Significance Paired T Test Z Score Table Assumed Mean Method Box and Whisker Plot Gamma Distribution Sample Size T Distribution Tests of Significance Types of Statistics Continuous Variable Sample Statistic Exponential Smoothing T Test Table Bivariate Analysis Relative Frequency Difference between Average and ...Difference between Mean and Med...Difference between Parametric a...Grouping data Statistics pdf Mean Absolute Deviation Population and Sample

Rachit Kumar SaxenaManager-Editorial

Updated on Aug 5, 2021 11:47 IST

Table of Contents

What is Data Grouping?
Weightage of Data Grouping in class 10:
Illustrated example on Data Grouping
FAQs on Data Grouping

What is Data Grouping?

When a large amount of data is analyzed and processed, it takes a lot of time and resources. To make the process of handling massive data easier, we group the data. Grouping of data is the method of separating information based on some parameters and placing similar data in a single group. All the data in one group has common characteristics and can be operated upon together.

Data grouping:

Representation of grouped data is essential to understand its characteristics. The pictorial form of representation of data is easier to understand and implement. We can use frequency distribution tables and histograms to present grouped data.

Frequency distribution:

The number of times an event occurs is known as its frequency. The frequency distribution for grouped data represents data for a group rather than a single value. The separate groups are known as class or class intervals. For a frequency distribution, the classes have a range of numbers. The number from where the range begins is known as the lower class limit, and the number till which the range exists is known as the upper-class limit. The difference between the upper and lower class limits is known as the size of the class interval. It is also referred to as the width of the class interval.

Histogram:

A histogram is a form of graphical representation of grouped data. It is similar to a bar graph, but instead of categorically distributed numbers representing discrete numbers, a histogram represents a range of categorically distributed numbers. On a histogram, the class intervals are represented on the horizontal axis or the x-axis. Also, there is no gap between the bars of a histogram as the data is divided into class intervals such that there is no difference between them.
The length of the bars of a histogram signifies the frequency of the class intervals.

Weightage of Data Grouping in class 10:

The topic-grouped data is introduced in classes 8 and 9. In class 10, the chapter- statistics involves the applications of these concepts. This carries a weightage of around 5-6 marks in the examination.

Illustrated example on Data Grouping

1. Here are the marks obtained by 50 students of class 9 in an examination. The maximum number of marks for the exam is 50.
23, 8, 13, 18, 32, 44, 19, 8, 25, 27, 10, 30, 22, 40, 39, 17, 25, 9, 15, 20, 30, 24, 29, 19, 16, 33, 38, 46, 43, 22, 37, 27, 17, 11, 34, 41, 35, 45, 31, 26, 42, 18, 28, 30, 22, 20, 33, 39, 40, 32.
What will be its frequency distribution?

Solution:

Groups	Frequency
0- 10	3
10- 20	11
20- 30	14
30- 40	14
40- 50	8
Total	50

This distribution obtained in the above table is referred to as the grouped frequency distribution.
In the above-obtained table, the groups 0-10, 10-20,... are known as class intervals. In class 10-20, 10 is the lower class limit, and 20 is the upper-class limit.

FAQs on Data Grouping

Q: What is grouped and ungrouped data?

A: The data or information that is not processed and is in its raw form is known as ungrouped data. The data that has been categorically distributed in segments is known as grouped data.

Q: How is data grouped?

A: To separate data into groups, a parameter is estimated. Then, based on this parameter, the data is assigned to various groups known as class intervals.

Q: How can we find the range of a class interval?

A: To find the class interval range, we subtract the lower class limit from the upper-class limit. This gives the width of the class interval.

Q: What are the central tendencies of ungrouped data?

A: Mean, mode, and median are the central tendencies of ungrouped data.

Q: What are the advantages of data grouping?

A: The advantages of data grouping are that they help us concentrate on crucial information and discard useless data. It also helps increase efficiency.