Classification and Tabulation of Data in Research

Classification is the way of arranging the data in different classes in order to give a definite form and a coherent structure to the data collected, facilitating their use in the most systematic and effective manner. It is the process of grouping the statistical data under various understandable homogeneous groups for the purpose of convenient interpretation. A uniformity of attributes is the basis criterion for classification; and the grouping of data is made according to similarity. Classification becomes necessary when there is diversity in the data collected for meaningful presentation and analysis. However, in respect of homogeneous presentation of data, classification may be unnecessary.

Objectives of classification of data:

  • To group heterogeneous data under the homogeneous group of common characteristics;
  • To facility similarity of various group;
  • To facilitate effective comparison;
  • To present complex, haphazard and scattered dates in a concise, logical, homogeneous, and intelligible form;
  • To maintain clarity and simplicity of complex data;
  • To identify independent and dependent variables and establish their relationship;
  • To establish a cohesive nature for the diverse data for effective and logical analysis;
  • To make logical and effective quantification

A good classification should have the characteristics of clarity, homogeneity, and equality of scale, purposefulness, accuracy, stability, flexibility, and unambiguity.

Classification is of two types, viz., quantitative classification, which is on the basis of variables or quantity; and qualitative classification (classification according to attributes). The former is the way of grouping the variables, say quantifying the variables in cohesive groups, while the latter group the data on the basis of attributes or qualities. Again, it may be multiple classification or dichotomous classification. The former is the way of making many (more than two) groups on the basis of some quality or attributes, while the latter is the classification into two groups on the basis of the presence or absence of a certain quality. Grouping the workers of a factory under various income (class intervals) groups comes under multiple classifications; and making two groups into skilled workers and unskilled workers is dichotomous classification. The tabular form of such classification is known as statistical series, which may be inclusive or exclusive.

The classified data may be arranged in tabular forms (tables) in columns and rows. Tabulation is the simplest way of arranging the data, so that anybody can understand it in the easiest way. It is the most systematic way of presenting numerical data in an easily understandable form. It facilitates a clear and simple presentation of the data, a clear expression of the implication, and an easier and more convenient comparison. There can be simple or complex tables, and general purpose or summary tables. Classification and tabulation are interdependent events in a research.