Classification

Introduction

            The collected data are a complex and unorganized mass of figures which is very difficult to analyse and interpret. Therefore, it becomes necessary to organize this so that it becomes easier to grasp its broad features.

Further, in order to apply the tools of analysis and interpretation, it is essential that the data are arranged in a definite form. This task is accomplished by the process of classification and tabulation.

Classification

            Classification is the process of arranging the available data into various homogeneous classes and subclasses according to some common characteristics or objective of investigation. In the words of L.R. Connor, “Classification is the process of arranging things in the groups or classes according to the unity of attributes that may subsist amongst a diversity of individuals.”

Characteristics of classification

1.      The collected data are arranged into homogeneous groups.

2.      The basis of classification is the similarity of characteristics or features inherent in the collected data.

3.      Classification of data signifies unity in diversity.

4.      Classification of data may be actual or notional.

5.      It should be unambiguous.

Objectives

            The main objectives of any classification are:

1.      To present a mass of data in a condensed form.

2.      To highlight the points of similarity and dissimilarity.

3.      To bring out the relationship between variables.

4.      To highlight the effect of one variable by eliminating the effect of others.

5.      To facilitate comparison.

6.      To prepare data for tabulation and analysis.

Types of classification 

            The nature of classification depends upon the purpose and objective of investigation. The following are some very common types of classification:

1.      Geographical classification

2.      Chronological classification

3.      Conditional classification

4.      Qualitative classification

5.      Quantitative classification

Geographical classification

            When the data are classified according to geographical location or region, it is called a geographical classification. E.g production of raw cotton in India may be classified on the basis of State wise

Chronological classification

            When the data are classified on the basis of its time of occurrence, it is called a chronological classification. Various time series such as; National Income figures, annual output of wheat, monthly expenditure of a household, daily consumption of milk, etc., are some examples of chronological classification.

Conditional classification

            When the data are classified according to certain conditions, other than geographical or chronological, it is called a conditional classification.

Qualitative classification

            When the characteristics of the data are non-measurable, it is called a qualitative data. The examples of non-measurable characteristics are sex of a person, marital status, colour, honesty, intelligence, etc. these characteristics are also known as attributes.

Quantitative classification

            In case of quantitative data, the characteristic is measurable in terms of numbers and is termed as variable, e.g., weight, height, income, the number of children in a family, the number of crime cases in a city, life of an electric bulb of a company, etc.