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d. Central editing: It is done by the researcher after getting
all schedules or questionnaires or forms from the enumerators or
respondents. Obvious errors can be corrected. For missed data
◆ Detecting errors and or information, the editor may substitute data or information by
omissions reviewing information provided by likely placed other respondents.
A definite inappropriate answer is removed and “no answer” is
entered when reasonable attempts to get the appropriate answer
fail to produce results.
4.1.2.2 Coding of Data

Coding is the process of categorising data according to research
subject or topic and the design of research. In the coding process
researchers set a code for a particular thing like male-(1), female-
(2) that indicates the gender in the questionnaire without writing
full spelling, just as researchers can use colours to highlight
something or numbers like 1+, 1-. This type of coding makes it easy
to calculate or evaluate results in tabulation. Codes are numerical.
Coding can be tedious if certain issues are not addressed prior to
◆ Assigning symbols collecting the data.

Four steps involved in coding:
i. Generate a list of as many potential responses as possible
ii. Consolidate responses

iii. Assign a numerical value as a code
iv. Assign a coded value to each response
4.1.2.3 Classification of Data

Classification or categorisation is the process of grouping
the statistical data into various understandable homogeneous
groups for the purpose of convenient interpretation. Uniformity
of attributes is the basic criterion for classification and the
grouping of data according to similarity. Classification becomes
necessary when there is diversity in the data collected for
meaningful presentation and analysis. However, it is meaningless
in respect of homogeneous data. A good classification should
◆ Logical grouping of have the characteristics of clarity, homogeneity, equality of
data scale, purposefulness and accuracy. Classification can be one of
the following two types- Classification according to attributes
and Classification according to class-intervals. In the case of
classification according to attributes, data having descriptive
characteristics such as literacy, sex, honesty, etc. are considered.
The classification according to class-intervals deals with numerical
data such as data relating to income, production, age, weight, etc.
Such data are known as statistics of variables and are classified on
the basis of class intervals.

The following are the objectives of classification:

146 SGOU - SLM -MCom Research Methodology