2. Introduction
• In this chapter proposal deals with methods for the
research.
• It will focus on:
What type of data will be needed (design)
How to get the data (data collection)
What to do with data once collected (data analysis)
3. Design
• Qualitative
• Unfolding Research
• Research is loosely
designed before going
to field
• Eg: loose/no hypothesis
• Research is designed
during field work
• Quantitative
• Pre-Structured Research
• Research is designed
before going to field
• Eg: hypothesis,
variables, conceptual
framework
4. Data Collection
• Qualitative
• Interview Guide
• Open ended
questions
• Quantitative
• Questionnaire
• Close ended
questions
6. Qualitative, Quantitative or Both
• Logic of a study including the way research question
or hypothesis are framed clearly shows whether it is
qualitative or quantitative
• That logic flows into the design, data collection and
data analysis.
7. • Example:
• Experimental comparison (cause and effect is
checked) it would be quantitative
• Ethnography (cultural significance of behavior) it
would be qualitative.
• Or mixed methods
• Example:
• Quantitative survey and also qualitative in-depth
interviews.
8. Design
• Research design accommodate both
qualitative and quantitative approaches.
• Research design means connecting
research question to data i-e what tools
and procedures will be used.
• Research design is the plan that tell how
research will be conducted.
9. Strategy
• A careful plain for achieving a particular
goal.
• Quantitative research design vary from
interventionist to non interventionist.
• Qualitative generally non interventionist.
12. Data Collection And Procedure
• How will the data be collected?
• Instruments – quantitative data
• Quantitative data collection instruments are
questionnaires, standardized measuring
instruments
• Instruments – qualitative data
13. Qualitative data are most likely to be words,
which we get by asking (interviewing), watching
(observation) or reading (documents)
14. Ethical issues
Data collection procedures need to be organized
both to maximize the quality of data, and to deal
with the related issues of access and ethics.
•Informed consent
•Privacy
•Ownership of data and conclusions
•Honesty and trust
•Harm and risk