This document discusses the process of data analysis, which includes editing, coding, classification, and tabulation of raw data collected during research. It explains that after data collection, the researcher must process and analyze the data. Key steps include editing the data for accuracy and completeness, coding the data by assigning numeric or alphabetic values to response categories, classifying the data into groups based on common attributes, and tabulating the data by organizing it into tables for further analysis and interpretation. Computer software can facilitate large-scale data processing and tabulation.

1.  DATA ANLYSIS
 BY ;
 Ms. KAVITHA. M. R

2. Introduction;
Once the data are collected with the
researcher turns his focus of attention on
their processing.
A researcher has to make his plan for each
and every stage of the research process.
As such, good researcher makes a perfect
plan of processing and analysis of data. To
some researchers data processing and
analysis is not a very serious activity.

3. Introduction;
Data process is an intermediary stage of work
between data collection and data analysis.
The collected data through various tools such
as interview schedule, questionnaires, data
sheets, and field notes contains a vast mass of
data.
And these collected information doesn’t gives
straight away answers to research questions.
The collected data is in raw materials, so it
needs processing.

4. Data processing consists of a
number of closely related
operations;
•Editing
•Coding and Classification
•Tabulation

5. Once the data is collected, then these
aspects to be followed very importantly
1. Checking the questionnaire Thorley.
2. Sorting out and reducing information collected to
manageable proportions.
3. Summarizing the data in tabular form.
4. Analyzing facts .
5. Interpreting the results or converting data into statements
,propositions or conclusion which ultimately will answer the
research questions.

6. Editing:
Editing of data is a process of examining the collected
raw data to detect errors and omissions and to
correct these when possible.
• a careful scrutiny of the completed questionnaires
and the schedule.
• Editing is done to assure that the data are accurate,
consistent with other facts gathered, uniformly
entered, as completed as possible and have been well
arranged to facilitate coding and tabulation.

7. The editing could be classified as;
1. Field editing and
2. central editing.

8. •Field Editing;
Field editing consists in the review of the reporting
forms by the investigator for completing (translating
or rewriting) what the letter has written in
abbreviated and or ill illegible form at the time of
recording the respondent’s response.
 it is done as soon as possible after the interview,
preferably on the very day or on the next day.
 field editing the investigator must restrain him and
must not correct errors of omission by simply
guessing what the informant would have said if the
question had been asked.

9. •Central Editing;
Central editing takes place when all forms or
schedules have been completed and returned
to the office.
 This can be done by individual in case of
small study, whereas in the larger studies a
team of editors will do the editing.

10. The editors would edit the inappropriate
on missing replies; the editor can
sometimes determine the proper answer
by reviewing the other information in the
schedule.
Sometimes the respondents can be
contacted for the clarifications.

11. Important aspects in the editing process are;
1. Completeness;
2. Accuracy;
3. Uniformity;

12. Coding ;
Coding process assigns numerals or other
symbols to the several responses of the
data set.
In simple coding is translating answers
into numerical values or assigning
symbols/ numbers to the various
categories of variables to be used in
data analysis.

13. Coding is necessary for efficient
analysis and through it the several
replies may be reduced to a small
number of classes which contain
the critical information required
for analysis.

14. A. Numerical coding;
Coding need not necessarily be
numeric, it can also be alphabetic.
Coding has to be compulsorily
numeric, when the variable is to be
subject to further parametric
analysis

15. B. Alphabetic coding;
A mere tabulation or
frequency count or
graphical representation of
the variable may be given
an alphabetic coding.

16. C. Zero coding;
A coding of zero has to be assigned carefully to a
variable.
In most of the cases when manual analysis is done, a
code of “0” would imply a “no response” from the
respondents.
Hence, if a value of 0 is to be given to a specific
response in the data sheet, it should not lead to the
same interpretation of “no response”.
For ex; there will be a tendency to give a code of 0 to
a “no” answer. However, if the respondent had not
chosen “yes’ or “no”, then a different coding than 0
should be given in the data sheet.

17. Question
number
Variable/observati
on
Response
categories
code
1.1 Organization Private Pt
Public Pb
Government Go
3.4 Owner of vehicle yes 2
No 1
4.2 Vehicle
performance
Excellent 5
Good 4
Adequate 3
Bad 2
Worst 1
5.1 Age Up to 20 years 1
21-40 years 2
40-60 years 3
Above 60 years 4
5.2 Occupation Salaried S
Professional P
Technical T
Business B
Retired R
House wife H

18. • Classification;
• The process of arranging data in
groups or classes on the basis of
common characteristics.
• Data having common characteristics
are placed in one class and in this way
entire data get divided into number of
groups or classes.

19. •Classification according to attributes :
The data are classified on the basis of common
characteristics which can either be descriptive
(such as literacy, sex, emotions, honesty) etc.
A descriptive characteristic refers to qualitative
phenomenon which cannot be measured
quantitatively; only their presence or absence in
an individual item can be noticed.
Data obtained this way on the basis of certain
attributes are known as statics of attributes and
their classification is said to be classification
according to attributes.

20. •Classification according to class-interval:
The numerical characteristics refer to
quantitative phenomenon which can be
measured through some stastical units.
Data retaining to income, production, age
weight etc.
Such data are called as stastics of variables and
are classified on the basis of class intervals.
For ex; persons whose income says are within
Rs 202-Rs 400 can form one group, those whose
incomes are within Rs 401- Rs 600 can another
group.

21. In the case of open ended questions
to classify responses the researcher
looks for major characteristics of the
responses and puts accordingly.

22. In case of attitude scales a researcher has to
keep in mind the direction or weightage of
responses.
Forex; when responses “strongly agree” is
coded as 5 the subsequent codes would be in
order.
Therefore, if there are responses like “agree”
“undecided” , “ disagree” and “ strongly
Disagree”, they have to be coded as 4,3,2, and
1.

23. The matrix questions have to be coded taking
into consideration each cell as one variable.
For ex; if the column of matrix represents
employment status, namely “permanent” and
“temporary” and the row represents employers
or type of employer, namely, government and
private, the first cell would represent a variable
“government permanent” .
The second cell would represent “government
temporary” and so on.

24. Tabulation:
Tabulation 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. It involves counting the number of
cases falling into each of the categories
identified by the researcher.
In a broader sense, tabulation is an orderly
arrangement of data in columns and rows. This
can be done manually or through computer.

25. Importance of Tabulation;
•It conserves space and reduce
explanatory and descriptive statement to
a minimum.
•It facilitates the process of comparison
•It facilitates the summation of items and
the detection of errors and omissions.
•It provides a basis for various statistical
computations.

26. computerized data processing;
When the sample size is large and or
when the variables studied is vast and
inter related data can be transcribed to
the computer for further easy
processing.

27. Computerized tabulation is easy with the help of
software packages. The input requirement will be the
column and row variables (EXCEL spread sheet).
The software package then computes the number of
records in each of the row/column categories. The
most popular package is the Statical Package for Social
Sciences (SPSS, Systat ).
It is an integrated set of programs suitable for analysis
of social science data.
This package contains programs for a wide range of
operations and analysis such as handling missing data
recording, variable information, simple descriptive
analysis, cross tabulation, multivariate analysis and
non-parametric analysis

28. Example of Master Sheet / CHART
The master sheets explain complete coding process of the collected data.
Respon
dents
Sl no.
No
Variable labels
Age desig
natio
n
Level
of
educ
atio
n
Marit
al
status
Natur
e of
work
Durati
on of
work
Wag
es
Attitude of
employer
1 A B D C D A A A
2 B A D C C A A E
3 C A D C E D E A
4 D E D C E A A C
5 E E A D B E C D

29. Some important points that can be
kept in mind while preparing the
coding for computerized data entry
are;
•Use a ‘natural ‘ coding scheme:
•Avoid the blank space as a coding
category.
Do not use the – “ “, +, symbols .

30. Presentation and
Interpretation of
Data.
Construction of
frequency table:

31. Components of tables:
The major components of a table are;
•Heading
•Table number
•Title of the table
•Designation of units
•Body
•Sub-head: heading of all rows or blocks of items
•Body head: headings of all columns or main captions
and their sub-captions.
•Field/body: the cells in rows and columns.
•Notations
• Footnotes, wherever applicable
•Source, wherever applicable

32. Types of tables;
•Uni-variate /One way tables
Uni-variate analysis refers to tables, which give
data relating to one variable.
Uni-variate tables, which are more commonly
known as frequency distribution tables, how
frequently an item repeats.
Further properties of distribution can be found
out by various measures of central tendencies.

33. Example
The below table showing awareness of the respondents
Level of
awareness
Distribution of respondents
Frequencies %
High 110 39.3
Medium 106 37.9
Low 64 21.8
Total 280 100.0

34. •Bi-variate /Two way table:
Distribution in terms of two or more variables and the relationship
between two variables are shown in two- way tables.
Example: table showing levels of awareness towards the Act and wage Differentials
of the Respondents.
Awareness
about the
ACT
Wage differentials
High Medium l Low Total
High 94(66.2) 99(10.5) 7(13.5) 110(39.3
)
Medium 37(26.1) 58 (67.4) 11(21.2) 106(37.9
)
Low 11(7.7) 86(30.7) 52(14.6) 280(100.
0)
Total 142 86 52 280(100.
0)

35. •Multi-variate Analysis:
If the researcher is interested in assessing the
joint effect of three or more variables, he uses
the techniques of multi-variate analysis.
The most common stastical technique used for
multi-variate analysis is regression analysis.
In the first step of multi-variable analysis, the
researcher has to obtain the correlation
between the variables which are having
stastically significant correlation.
These variables are put in the regression
analysis.

36. Diagrammatic Representation:
A diagram helps to understand the data easily. All stastical packages, MS
Excel and Open Office offer a wide range of graphs. In case of qualitative
data most common graphs are bar charts and pie charts.
The most commonly used graphic forms may be grouped into the
following categories;
Graphs
Histogram & Bar charts
Pie chart
Pictogram
Pyramid Diagram

37. • Graph:
The graph offers a visual presentation
of the results.
The line graph can also provide
markers for each data point marker for
each variable can be different to
distinguish it from other variables. The
marker also highlights the value at any
specific point

38. 14
12
10
8
6
4
2
0
Category 1 Category 2 Category 3 Category 4
Series 3
Series 2
Series 1

39. •Histograms
Histograms and bar charts have two axes that intersect at right angles.
One axis (horizontal one) is divided into intervals representing the
various possible values of the variables. The other axis (vertical one) is
divided into intervals representing frequencies. Histogram depicts the
data graphically with vertical bars adjacent to each others.
6
5
4
3
2
1
0
2 4 6 8 10

40. Bar chart:
Bar charts are similar to histograms except that
the bars are separated. Bar charts can be used
for nominal level data to show different
variables. Ex, diagram;
7
6
5
4
3
2
1
0
1 2 3 4
Series 3
Series 2
Series 1

41. Pie charts:
Pie charts are circular charts divided into slices. Each slice
represents a possible score and its size is proportional to
occurrence of those scores in the sample. The component
parts from the segments of the circle. The circle chart is
usually a percentage chart. The data are converted to
percentage of the total and the proportional segments;
therefore give a clear picture of the relationship among the
components.
1.4
1.2
3.2 8.2
1st Qtr
2nd Qtr
3rd Qtr
4th Qtr

42. • Pictogram:
Each picture represents (man, animal, vehicles, crops,) a
certain number and total number of pictures gives the total
number of events/ elements. Pictograms are an exciting way
to summaries data and are often used in newspapers.
Examples for pictogram;

44. •Pyramid diagram;
Pyramid consists of many levels and presents one or two
variables.

45. RESEARCH REPORT
The final and very important step in a research study is to
write its report. The research report is a means for
communication our research experiences to others and
adding them to the fund of knowledge.

46. Functions of research report;
•It serve as a means for presenting the problem studied,
methods and techniques used for collecting and analyzing
data, the findings , conclusions and recommendations in an
organized manner.
•It serves as a basic reference material for future use in
developing research proposal in the same or related area.
•A report serves as a means for judging the quality of the
completed research project.
•It is a means for evaluating the researcher’s ability and
competence to do research.
•It provides factual base for formulating policies and
strategies relating to the subject matter studied.
•It provides systematic knowledge on problems and issues
analyzed.

47. Different steps in writing report:
•Logical analysis of the subject matter;
•Preparation of the final out line
•Preparation of the rough draft
•Rewriting and polishing of the rough
draft
•Preparation of the final bibliography
•Writing the final draft

48. Planning report writing;
•The target audience
•The communication characteristic of
audience.
•The intended purposes of the report
•The type of report
•The scope of the report
•The style of reporting
•The format of report
•Outline/time table of the report

49. BIBILOGRAPHY;
•Methodology of research in social sciences –
Dr.O.R. Krishnaswami, Himalayan publishing house,
1999.
•Research for social workers ,An introduction to
methods, 2nd edition
Margaret Alston , Wendy Bowles
•Research Methodology Methods and techniques
(Second Revised Edition 2004) & third edition 2014.
C. R. Kothari, New Age International Publishers.
•Practice of social research – social work perspective
D.K.Lal Das
Rawat publication, 2004.

50. THANK YOU