Classification of Data:
What is Classification of Data?
The collected data, also known as
raw data or ungrouped data are always in an unorganised form and need to be
organised and presented in meaningful and readily comprehensible form in order
to facilitate further statistical analysis. It is, therefore, essential for an
investigator to condense a mass of data into more and more comprehensible and
assimilable form.
The process of grouping into
different classes or sub classes according to some characteristics is known as
classification, tabulation is concerned with the systematic arrangement and
presentation of classified data. Thus classification is the first step in
tabulation.
For Example, letters in the post
office are classified according to their destinations viz., Delhi, Madurai,
Bangalore, Mumbai etc.,
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| Classification of Data |
Objectives of Classification of Data:
The following are main objectives
of classifying the data:
1. It eliminates unnecessary
details.
2. It facilitates comparison and
highlights the significant aspect of data.
3. It enables one to get a mental
picture of the information and helps in drawing inferences.
4. It helps in the statistical
treatment of the information collected.
Types of classification of Data:
Statistical data are classified
in respect of their characteristics. Broadly there are four basic types of
classification namely
a) Chronological classification
b) Geographical classification
c) Qualitative classification
d) Quantitative classification
Chronological
classification:
In chronological classification
the collected data are arranged according to the order of time expressed in
years, months, weeks, etc., The data is generally classified in ascending order
of time. For example, the data related with population, sales of a firm, imports
and exports of a country are always subjected to chronological classification.
- Geographical
classification:
In this type of classification the
data are classified according to geographical region or place. For instance,
the production of paddy in different states in India, production of wheat in
different countries etc.,
- Qualitative
classification:
In this type of classification data
are classified on the basis of same attributes or quality like sex, literacy,
religion, employment etc., Such attributes cannot be measured along with a
scale.
For example, if the population to
be classified in respect to one attribute, say sex, then we can classify them
into two namely that of males and females. Similarly, they can also be
classified into ‘employed’ or ‘unemployed’ on the basis of another attribute ‘employment’.
Thus when the classification is
done with respect to one attribute, which is dichotomous in nature, two classes
are formed, one possessing the attribute and the other not possessing the attribute.
This type of classification is called simple or dichotomous classification.
A simple classification may be
shown as under
Population
Male Female
The classification, where two or
more attributes are considered and several classes are formed, is called a
manifold classification. For example, if we classify population simultaneously
with respect to two attributes, e.g sex and employment, then population are first
classified with respect to ‘sex’ into ‘males’ and ‘females’.
Each of these
classes may then be further classified into ‘employment’ and ‘unemployment’ on
the basis of attribute ‘employment’ and as such Population are classified into
four classes namely.
(i) Male employed
(ii) Male unemployed
(iii) Female employed
(iv) Female unemployed
Still the classification may be
further extended by considering other attributes like marital status etc. This
can be explained by the following chart
Population
Male
Female
Employed Employed
UnEmployed UnEmployed
- Quantitative
classification:
Quantitative classification
refers to the classification of data according to some characteristics that can
be measured such as height, weight, etc.,