Types of data collection. Sources of data collection. Qualitative and quantitative. primary and secondary. Questionnaires. Types of responses: dichotomous responses, trichotomous responses. Multiple choice, and Likert's scale. We discussed reliability and validity. Specificity and sensitivity of the tools. Application of Likert's scale in daily practical life. Aptitude test and its usage in daily life. Administering of Kuppuswamy scale for assessing socio-economic scales.

1. Methods of Data Collection: Part-I
Dr. Rajeev Kumar
M.S.W., (TISS, Mumbai), M.Phil., (CIP, Ranchi), UGC-JRF., Ph.D., (IIT Kharagpur)
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2. How to choose your topic of research project?
Your area of
interest and
competency
Available time,
resource, facilities,
and data
Academic area
interest and
competence of
your guide
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3. Stages of research project/ Dissertation progress
First Phase: Preparatory
stage
Choose broad theme
Broad literature review
and pilot visits
Narrow research topic and
substantial literature review
Identify gaps and define
research question
Make objectives
Design data collection
tools
Second phase: Field work
Translation of data
collection tool in Hindi
(10%) Do pilot testing of
tool
Modify your tool after
pilot visit
Do final data collection
Content analysis
Coding of open ended
responses
Third phase: Report
writing
Tabulation
Statistical analysis
Data cleaning
Chapterization
Enter data in Excel
Export to SPSS
Finalize and submit
the dissertation
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9. Some common source of secondary data
• Reports of United nation organizations
• Census reports
• NFHS (National Family health survey)
• NSS (National Sample survey) reports
• SRS (Sample registration system) reports
• Reports of prominent organizations
• Reports of Ministries
• Data of previous researches
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10. Example of Secondary data interpretation-1
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11. Example-2: secondary data interpretation
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12. Preparing research protocol
Design
Source of
data
Approach of
data
Longitudinal
Cross-
sectional
Experimental
Retrospective
or
prospective
cohortPrimary data
Secondary
data
Qualitative
Q2: Mixed
Quantitative
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19. Example of Questionnaire. (1) Open ended (2)
close ended (3) Close ended: Dichotomous (4)
close ended: Likert scale
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Now identify the closed ended and open ended responses

20. Identify types of data and responses
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21. Rating scales (Ready made tools or
standardized scales)
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22. Likert’s scales
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23. We often see the examples of Likert’s scale in our
practical life
How responses are measured?
(5 Point Likert’s scale)
Straight scoring
A. Very poor=1, Poor=2,
OK=3, Good=4, Very
good=5
B. Very poor=0, Poor=1,
OK=2, Good=3, Very
good=4
Reverse scoring
C. Very poor=5, Poor=4, OK=3,
Good=2, Very good=1
D. Very poor=4, Poor=3, OK=2,
Good=1, Very good=0
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24. Rating scales: Measures the severity
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25. We can do screening using GHQ-12 (General
Health Questionnaire)
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26. All of them are readymade standardized scales. And need
reliability and validity establishment
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27. An easy understanding of reliability and
validity of tools
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28. Where does reliability and validity come?
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29. How do we interpret reliability and validity?
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30. Aptitude test: Example of standard tools
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31. PABT: It happens once in a life
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32. What happens when we use instruments?
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33. Sensitivity and Specificity: A game of true and
false
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34. True positive, false positive, true negative and
false negative
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35. How to calculate sensitivity ?
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36. Meaning of sensitivity and specificity
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37. In News: Sensitivity and Specificity
PPA (Percent positive agreement) PNA (percent negative agreement)
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40. Assessment of education level
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41. Assessment of monthly income
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42. Kuppuswamy scale: Assessment of occupation
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44. Summary: how to chose data collection tool?
• Questions should be related to your objectives
• And objective should come out of theme of research or research
questions or hypothesis.
• We must think proper, as how the responses and questions should be
enter the computer software (SPSS, MS Excel, Epi-info etc.,)
• However, it is recommended always use MS excel
• The template of MS excel should match questionnaire or tool
• All the responses should be already codified
• However, open ended responses, we can codify later.
• While making tool, we must have a broad idea of statistical analysis
(descriptive, analytical)
Analytical: chi square, T test, correlation, regression etc.,
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45. Thanks for your kind attention
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