Basic Concept of Data & Variables

Primary data : It is originated by the investigator himself for some specific purpose.

Secondary data : It is obtained from the records of some one else.

Survey data : It is already available and can be collected and recorded by observation or inquiry

Experimental data : It is obtained with the help of well-designed statistical experiments.

Variable

A set of observations on a particular character is termed a variable.

Variable is a character under observation whose value varies from individual to individual and from time to time in the same individual.

Classification of data

•Classification by source of data

–Primary (collected by the investigator himself)

–Secondary (already collected by someone else)

Primary data is further classified based on Method of collection

1. Direct observation

2. Interviews

3. Questionnaires

4. Experiments

Secondary data is further classified based on its Sources

1.Published (Government documents, Technical reports, Scholarly journals etc.)

1.Unpublished (records maintained by various Government and private offices, studies made by research institutions etc.)

•Classification by Type of data

1.Qualitative (attributes or non-measurable characteristics e.g. Sex, health etc.)

2.Quantitative (According to numerical size like weights, heights etc.)

•Classification of statistical data

1.Time series or temporal data (Collection of data over a period of time e.g. production of milk, wool, meat and eggs, etc., during different years )

2.Spatial or geographical data (Collected according to a geographical region e.g. population and birth or death rates of a country according to states)

3.Spacio-temporal data (Collected according to time as well as place e.g. milk production of Murrah buffaloes in Punjab, Rajasthan, Maharashtra and Madhya Pradesh during the years 2013, 2014, 2015 and 2016)

Variable

Classification of Variables

Quantitative variables : Differing states can be expressed in a numerically ordered fashion e.g. Weight of animals, milk yield etc.

1. Continuous variables: Can take up any numerical value (integral/fractional) within a certain range e.g. milk yield, milk fat content etc.

2. Discontinuous or discrete variables: can take up only exact values (not any fractional values) e.g. number of offspring or litter size etc.

Qualitative variables : Cannot be measured but must be expressed qualitatively, numerical measurement is not possible e.g. black and white, dead or alive etc.

1. Nominal variable : Categories that cannot be ranked, values fall into unordered categories e.g. milk yield, milk fat content etc.

2. Ordinal variable : Categories can be ranked e.g. whether the government of Delhi should impose an odd-even driving. Responses may be do not agree, agree to some extent, agree to a large extent and totally agree, etc.

Ranked variables : Variables cannot be measured, but at least can be ordered or ranked by their magnitude e.g. we can rank individuals on the basis of their performance, say cows on their milk yield, students on their marks etc.

Derived variables : Variables are generally based on two or more independently measured variables whose relations are expressed in a certain way e.g. ratios, percentages, indices, etc.