DATA, CODING AND TABULATION

1. Presentation on Data
Editing, Coding and
Tabulation

2. Contents
 INTRODUCTION
 DATA EDITING
 NEED OF DATA
EDITING
 ESSENTIALS OF DATA
EDITING
 STAGES OF DATA
EDITING
 CODING OF DATA
 TABULATION
 OBJECTIVES
 COMPONENTS OF
TABLE
 TYPES OF
TABULATION
 SUMMARY
 REFERENCES

3. Introduction
The data collected from the
respondents is generally not in the
form to be analyzed directly. After
the response are recorded or
received, the next stage is of
preparation of data i.e. to make the
data amenable for appropriate
analysis.
Data preparation includes editing,
coding and tabulation and is the
activity that ensures the accuracy
of the data and their conversion
from raw form to reduced and
classified forms that are more
appropriate for analysis.
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4. The editing of data is a
process of examining the
raw data to detect errors
and omissions to correct
them, if possible, so as to
ensure legibility,
completeness, consistency
and accuracy.
The recorded data must be
legible so that it could be
coded later. An illegible
response may be corrected
by getting in touch with
people who recorded it or
alternatively it may be
inferred from other parts of
the question.
Data Editing

5. Example
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 Information gathered during data collection may lack uniformity.
e.g.- Data collected through questionnaire and schedules may
have the answers which may not be ticked at proper place, or
some questions may be left unanswered. Sometimes information
may be given in a form which needs reconstruction in a category
designed for analysis, e.g., converting daily / monthly income in
annual income and so on.
The researcher has to take decision as to how to edit it.

6. Need of data editing
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1.Clarify Responses: With editing the data the researcher makes sure
that all responses are now very clear to understand. Bringing clarity is
important otherwise the researcher can draw wrong inferences from the data.
Sometimes the respondents make some spelling and grammatical mistakes
the editor needs to correct them. The respondents might not be able to
express their opinion in proper wording. The editor can rephrase the
response, but he needs to be very careful in doing so. Any bias can be
introduced by taking the wrong meanings of the respondent's point of view.
2.Make Omissions: The editor may also need to make some omissions
in the responses. By chance or by some mistake some responses are left
incomplete, the editor has to see what has been an oversight by the
respondent. It depends on the target population how well you get the
questionnaires filled. An educated respondent will fill the questionnaire in a
better manner than a person who is not very educated. It also depends on how
much interested the respondent is in filling the questionnaire. Sometimes the
respondents are very reluctant to fill it out.

7. Contd..
3.Avoid Biased Editing:
The editor has a great responsibility to edit the surveyed
data or other form of responses. The editor needs to be very
objective and should not try to hide or remove any
information. He should not add anything in the responses
without any sound reason. He should have to be confident in
making any changes or corrections in the data. In short, he
should make least changes and only logical changes. He
should not add anything that shows his opinion on the issue.
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8. Essentials of data editing
1)Completeness:
For effective editing, it should be considered that there are no omissions.
Therefore, it is essential that all the questions have been asked and the
corresponding responses have been recorded respectively. In case, any data is
missing, the researcher either can deduce the missing data based on other data
in the questionnaire, or can fill the data by recalling it.
2) Accuracy:
Data editing should be done keeping in mind, that the data recorded should be
accurate. Researchers must check the reliability of answers during the data
collection itself, which is not possible every time. Accuracy of the responses
can be estimated with the help of 'check questions' included in the
questionnaire specifically for important data. 'Check questions' can either
directly estimate the ambiguity of the response. or can help the researcher to
deduce the correct responses. Researchers can also conclude the response
with the help of other related questions in the questionnaire. Sometimes,
researchers can also contact the respondents again to get the correct
response.
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9. Contd…
3) Consistency: An important consideration while editing
the data is, maintaining consistency in responses. It should
be checked that answers are given in the same manner the
questions have been asked. In other words, all the responses
for a question should be answered in a similar way by all
respondents. Since, the inappropriate and inadequate
answers create confusion and wrong interpretation; hence
the researchers should make sure that the responses lead to
proper conclusions.
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10. Stages of data editing
1.Field Editing:
Field editing is performed during the data collection. All the responses
collected are checked for errors and omissions. While, collecting the data, the
researchers instantly check for accuracy, uniformity and completeness of the
answers. Field editing can be done in two ways :
 By the Researcher: Due to shortage of time, researchers while
taking interviews, note down the responses in the form of symbols or short
notes. After completion of the interview, researcher reviews the answers ,
corrects them if necessary, and completes the questionnaire by specifying
the answers to each question.
 By the Supervisor: Another form of field editing is done by the
supervisor of the team of interviewers appointed for collecting the data
from a sample of respondents. The supervisor maintains quality of data by
ensuring that all interviewers complete their task honestly. This is done by
checking and reviewing the responses of the interviews and correcting the
errors at the first stage itself.
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Contd…
2) Office/Central Editing:
When all completed forms are brought at the central
office, an individual or a team of individuals performs the
editing activities on these forms. This process is called
'office editing’ or "central editing'. Office editing is much
accurate than field editing. It is more suitable for mail
surveys as field editing cannot be performed in this case,
unlike the questionnaires and interview schedules.

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Coding is the process of assigning some symbols (either)
alphabetical or numerals or (both) to the answers so that the
responses can be recorded into a limited number of classes or
categories.
Example:
What is your sex? Male or Female
We may assign a code of `0' to male and `1' to female respondent. These codes may
be specified prior to the field work and if the codes are written on all questions of a
questionnaire, it is said to be wholly precoded.
What is your monthly income?
< Rs. 5000
Rs. 5000 – 8999
Rs. 13000 – 12999
Rs. 13000 or above.
We may code the class less than Rs.5000' as 1', Rs. 5000 - 8999' as `2', `Rs. 9000 -
12999' as `3' and `Rs. 13000 or above' as `4'
CODING OF DATA

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15. Tabulation
It is the process of summarizing raw data and
displaying the same in compact form(i.e. in the form
of statistical tables) for further analysis.
In a broader sense, tabulation is an orderly
arrangement of data in columns and rows.
Objectives:
 To do comparison
 To locate omission and error in data
 To simplify data
 Provides overview

16. Components of table
 Table number
 Title of the table
 Caption or column headings
 Stubs or row designation
 Body of the table
 Foot notes
 Sources of data

17. Types of tabulation
 Based on purpose of study:
 General purpose table
 Special purpose table
 Based on number of characters used:
 Uni-variate
 Bi-variate or multivariate

18. Contd…
Uni-variate tabulation

19. Contd…
 Bi-variate or multivariate tabulation

20. summary
After the data have been collected, the researcher turns
to the task of analyzing them. The data, after collection,
has to be processed and analyzed in accordance with the
outline laid down for the purpose at the time of developing
the research plan. This is essential for a scientific study
and for ensuring that we have all relevant data for making
contemplated comparisons and analysis. The analysis of
data requires a number of closely related operations such
as establishment of categories, the application of these
categories to raw data through coding, tabulation and
then drawing statistical inferences. The unwieldy data
should necessarily be condensed into a few manageable
groups and tables for further analysis. Thus, a researcher
should classify the raw data into some purposeful and
usable categories. Coding operation is usually done at
this stage through which the categories of data are
transformed into symbols that may be tabulated and
counted. Editing is the procedure that improves the
quality of the data for coding. With coding the stage is
ready for tabulation. Tabulation is a part of the technical
procedure wherein the classified data are put in the form
of tables. The mechanical devices can be made use of at
this juncture. A great deal of data, especially in large
inquiries, is tabulated by computers.
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21. References
 Unit-9.pdf (egyankosh.ac.in)
 Processing of Data,MBA-II Sem.pdf (mmhapu.ac.in)
 Data Processing: Editing, Coding, Tabulating
(theintactone.com)

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THANK YOU