Basics of the Qualitative Research is discussed. Differentiate between qualitative and quantitive research.

1. Qualitative Research
Dr. Akmal Samsor
asamsor@jscs.af

2. Session Objectives
At the end of the session participants will be
able to :
• Define Qualitative Research
• Differentiate between qualitative and
quantative research
• Understand the sampling and sample size for
qualitative research
• Name qualitative techniques for qualitative
data analysis

3. What is Qualitative Research?
‘Qualitative data refers to all non-numeric data
or data that have not been quantified and can
be a product of all research strategies’
Saunders et al. (2009)

4. What is Qualitative Research?
• “Qualitative research, with its focus on the
experiences of people, stresses the uniqueness
of individuals…qualitative researchers collect
data from their respondents, often in their
natural environments, taking into account how
cultural, social and other factors influence their
experiences and behaviour” (Parahoo 1997)

5. What can it be used for?
Qualitative Research is used to ascertain people’s
:
• Feelings
• Opinions
• Behaviours – reasons for
• Attitudes/ beliefs
• Problems
• Areas of need/ gaps in services

6. Qualitative Vs. Quantative
• Quantitative
– Objective
– Numeric
– Statistical analysis
– Large Ns
– Structured data
collection
– Table/graphs to display
results
• Qualitative
– Subjective
– Non-numerical
– Non-statistical analysis
– Small Ns
– Open ended data
collection
– Narrative for results

7. Sampling Methodology
• Non Probability Sampling is used :
– Convenience Sampling
– Quota Sampling
– Expert Sampling
– Purposeful Sampling
– Snowball Sampling
– Heterogeneity Sampling
– ….

8. Qualitative Sample Size Calculation
• Method for calculation of sample size not
clear
• Saturation level is the key

9. Qualitative Sample Size Calculations

10. Qualitative Sample Size Calculation
• But when do we reach a saturation level ?
• Some rules that are used in qualitative sample
size calculation :
– Key Informant Interviews (KII) per group=5
– In-Depth Interviews per group =30
– Focus Groups Discussion (FGDs) per group= 1
• Usually with the above mentioned sample size
saturation level is obtained.

11. Methods of Data Collection
• Interviews- structured or semi-structured,
guided, unstructured
• Focus groups- researcher(s) plus 5-10
participants - guided group discussion on topic(s)
• Telephone interviews
• Observation - researcher may be just observing
or sometimes more part of the group -
“participant observation”
• Covert observation - two-way mirrors or hidden
camera

12. 12

13. Analysis Methodology
These include:
• Grounded Theory
• Thematic analysis
• Content Analysis
• ……

14. Analysis Methodology
Grounded theory- A research method in which the
theory is developed from the data, rather than the
other way around. That makes this an inductive
approach, meaning that it moves from the specific to
the more general.
• The method of study is essentially based on three
elements: concepts, categories and propositions, or
what was originally called “hypotheses”. However,
concepts are the key elements of analysis since the
theory is developed from the conceptualization of
data, rather than the actual data.

15. Analysis Methodology
• Thematic analysis- Focuses on identifiable
themes and patterns of living and/or
behaviour. From the conversations that take
place in a therapy session or those that are
encouraged for the sake of researching a
process, ideas emerge that can be better
understood under the control of a thematic
analysis.

16. Analysis Methodology
• Content Analysis- Is doing the word-
frequency count. The assumption made is that
the words that are mentioned most often are
the words that reflect the greatest concerns.

17. Stages of Qualitative Data Analysis
Miles and Huberman (1994) suggest that
qualitative data analysis consists of three
procedures:
1. Data Reduction
2. Data Display
3. Drawing Conclusions

18. Stages of Qualitative Data Analysis
1. Data reduction. This refers to the process
whereby the mass of qualitative data you
may obtain – interview transcripts, field
notes, observations etc. – is reduced and
organised, for example coding, writing
summaries, discarding irrelevant data and so
on.

19. Stages of Qualitative Data Analysis
2. Data display. To draw conclusions from the
mass of data, Miles and Huberman suggest
that a good display of data, in the form of
tables, charts, networks and other graphical
formats is essential. This is a continual
process, rather than just one to be carried out
at the end of the data collection.

20. Stages of Qualitative Data Analysis
3. Conclusion drawing/verification. Your
analysis should allow you to begin to develop
conclusions regarding your study. These
initial conclusions can then be verified, that is
their validity examined through reference to
your existing field notes or further data
collection.

21. Steps of Qualitative Data Analysis
1. Coding the Data
2. Organizing the Data
3. Displaying the Data
4. Drawing Conclusions

22. Steps of Qualitative Data Analysis
• Coding is the organisation of raw data into
conceptual categories. Each code is effectively
a category or ‘bin’ into which a piece of data
is placed.

23. What should I look for when I have coded my
data ?
• You should look for patterns or regularities that occur.
• Within each code, look for data units that illustrate or
describe the situation you are interested in.
• Try to identify key words or phrases, such as
‘because’, ‘despite’, ‘in order to’, ‘otherwise’ and so
on and try to make sense of the data.
• Look for statements that not only support your
theories, but also refute them.
• Try to build a comprehensive picture of the topic.

24. What should I look for when I have coded my
data ?
• What type of behaviour is being demonstrated?
• What is its structure?
• How frequent is it?
• What are its causes?
• What are its processes?
• What are its consequences?
• What are people’s strategies for dealing with the
behaviour?

25. Steps of Qualitative Data Analysis
• Organizing the Data: Coded data may then be
organised as suggested by Biddle et al. (2001)
whereby the data units (statements, sentences, etc.)
are clustered into common themes (essentially the
same as codes), so that similar units are grouped
together into first order themes, and separated away
from units with different meaning.
• The same process is then repeated with the first order
themes, which are grouped together into second
order themes.

26. The ordinary wood… has the
ultimate feel, it feels like it’s a
golf club that you're very
much in control of, rather than
its in control of you.
The whole club swung very
well, it felt nice. You felt as if
you were in control.
… just feels as though I'm in
control of the clubhead right
throughout the shot.
I feel that I've no control over
that clubhead at all.
This feels much more difficult
to control…
…but I could not control it due
to the length and the flex of
the shaft.
Controllable
feel
Uncontrollable
feel
Club
control
Raw data
themes
Higher order
themes
General
dimensions

27. How do people travel to university?
Car Bus Train Bike Walk
Motorised Un-motorised
Distance influences
transport mode decisions
Poor personal mobility is
allied to motorised modes
Transport decisions are highly personalised
G
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28. Important Point
At no stage are numbers assigned to any category.
As Krane et al. (1997, p.214) suggest:
Placing a frequency count after a category of
experiences is tantamount to saying how important
it is; thus value is derived by number. In many cases,
rare experiences are no less meaningful, useful, or
important than common ones. In some cases, the
rare experience may be the most enlightening one.

29. Thank You
• More on Qualitative Data Analysis in the Next
Workshop Inshallah !!