Organisation of Data — Economics STD 11 Commerce — Question

Generally, data are classified on the basis of the following four bases: Geographical Classification: In geographical classification, data are classified on the basis of geographical or locational differences – such as cities, districts, or villages – between various elements of the data set. The following is an example of a geographical distribution. (Figures are hypothetical)

States of India	Punjab	Haryana	J & k	Bihar	Orissa	M.P.
Poverty (%)	12	10	3.5	39	38	34

Chronological Classification: When data are classified on the basis of time, the classification is known as chronological classification. Such classifications are also called time series because data are usually listed in chronological order starting with the earliest period. The following is an example of a Chronological distribution. (Figures are hypothetical)

Year	1951	1961	1971	1981	1991	2001
Poverty (%)	52	50	47	38	36	26

Another example can be:

Month	Family expenditure per member
January	2000
February	3000
March	1000
April	1200
May	2300
June	1400
July	1100
August	4300
September	900
October	1900
November	2100
December	3100

Qualitative Classification: In qualitative classification, data are classified on the basis of descriptive characteristics or on the basis of attributes like sex, literacy, region, caste, or education, which cannot be quantified. This is done in two ways: Simple classification: In this type of classification, each class is subdivided into two sub-classes and only one attribute is studied, for example male and female; blind and not blind, educated and uneducated; and so on. Manifold classification: In this type of classification, a class is subdivided into more than two subclasses which may be sub-divided further. An example is given below:
Quantitative Classification: In this classification, data are classified on the basis of characteristics which can be measured such as height, weight, income, expenditure, production, or sales. An example is given below:

Salary Per Month	No. of workers
0-10000	40
10,000-20,000	10
20000-30000	13
30000-40000	8
40,000-50,000	12
50,000 and above	7