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Unit 3: Classification and Tabulation of Data: Frequency and Cumulative Frequency Distribution
Pavitar Parkash Singh, LPU

Unit 3: Classification and Tabulation of Data: Frequency and Notes

Cumulative Frequency Distribution

CONTENTS
Objectives
Introduction
3.1 Classification
3.2 Tabulation of Data
3.3 Frequency Distribution
3.4 Cumulative Frequency Distribution
3.5 Summary
3.6 Key-Words
3.7 Review Questions
3.8 Further Readings

Objectives

After reading this unit students will be able to:
• Describe the Classification and Tabulation of Data.
• Understand Frequency Distribution.
• Explain Cumulative Frequency Distribution.

Introduction

The data collection leaves an investigator with a large mass of information. But it is the weakness of
human mind that it fails to assimilate a lot of things or information at a time. To remove this difficulty
and to make the large mass of data useful to its fullest, classification and tabulation of data is done.
By doing so the data are presented in condensed form which helps in making comparisons, analysis
and interpretations. Moreover, classification and tabulation segregates the likes from the unlikes.
The heterogeneity is removed. The data are classified into classes and sub-classes according to their
characteristics. This process is called classification. The classified data are presented in prescise and
systematic tables. This process is called tabulation. By these two processes, the data collected are
made simple, easy to understand and carry out analysis and interpretations.
3.1 Classification

Meaning and Definition of Classification
Classification may be defined as the process of arranging the available data in various groups or
classes in accordance with their resemblances and similarities and keeping in view some common
features and objectives of study. Thus, through classification, an effort is made to achieve homogeneity
of the collected information. While classifying, the units with common characteristics are placed
together and in this way the whole data is divided into a number of classes and sub-classes. It may be
argued that the data collected is as per the requirement, and it is in general homogeneous in nature,
then how does classification help ? For example, if a study on 500 students is to be carried out then,
the data is homogeneous as it is about students. But this information on 500 students may be classified
in terms of different hostels and universities they are coming from, different areas they come from,
different subjects they have opted for, and so on. Only by carrying out the one, classification, will the
invesitgator be in a position to compare, analyse and interpret the above data.

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