It may be defined as the process of arranging data on the basis of the characteristic under consideration into a number of groups or classes according to the similarities of the observations.

Following are the objectives of classification of data :

(i) It puts the data in a neat, precise and condensed form so that it is easily understood and interpreted.

(ii) It makes comparison possible between various characteristics, if necessary, and thereby finding the association or the lack of it between them.

(iii) Statistical analysis is possible only for the classified data.

(iv) It eliminates unnecessary details and makes data more readily understandable.

We can broadly classify data as given below :

(a) Primary

(b) Secondary

Collection of data plays the very important role for any statistical analysis. The data which are collected for the first time by an investigator or agency are known as primary data whereas the data are known to be secondary if the data, as being already collected, are used by a different person or agency.

Thus, if Prof. David collects the data on the height of every student in his class, then these would be primary data for him. If, however, another person, say, Professor John uses the data, as collected by Prof. David, for finding the average height of the students belonging to that class, then the data would be secondary for Prof. John. 

Collection of Primary Data :

The following methods are employed for the collection of primary data:

(i) Interview method;

(ii) Mailed questionnaire method;

(iii) Observation method.

(iv) Questionnaires filled and sent by enumerators.

Sources of Secondary Data :

There are many sources of getting secondary data. Some important sources are listed below:

(i) International sources like WHO, ILO, IMF, World Bank etc.

(ii) Government sources like Statistical Abstract by CSO, Indian Agricultural Statistics by the Ministry of Food and Agriculture and so on.

(iii) Private and quasi-government sources like ISI, ICAR, NCERT etc.

(iv) Unpublished sources of various research institutes, researchers etc.

Classification of Data

Data may be classified as -

(i) Chronological or Temporal or Time Series Data;

(ii) Geographical or Spatial Series Data;

(iii) Qualitative or Ordinal Data;

(iv) Quantitative or Cardinal Data.

Chronological or Temporal or Time Series Data

When the data are classified in respect of successive time points or intervals, they are known as time series data. The number of students appeared for CA final for the last twenty years, the production of a factory per month from 1990 to 2005 etc. are examples of time series data.

Geographical or Spatial Series Data 

Data arranged region wise are known as geographical data. If we arrange the students appeared for CA final in the year 2005 in accordance with different states, then we come across Geographical Data.

Qualitative or Ordinal Data

Data classified in respect of an attribute are referred to as qualitative data. Data on nationality, gender, smoking habit of a group of individuals are examples of qualitative data. Lastly, when the data are classified in respect of a variable, say height, weight, profits, salaries etc., they are known as quantitative data.

Quantitative or Ordinal Data

Data may be further classified as frequency data and non-frequency data. The qualitative as well as quantitative data belong to the frequency group whereas time series data and geographical data belong to the non-frequency group.

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