CHAPTER-9-Qualitative-data-analysis-and-interpretation-1.ppt

Qualitative (categorical) data represent characteristics or categories rather than numerical values.
Examples:

Gender (male/female),

Smoking (yes/no),

Type of therapy (A, B, C).

1. Welcome

2. Dates of tutorials
11 Oct 17:30-20:00
18 Oct 17:30-19:30
25 Oct 17:30-19:30
26 Oct EXAM

3. The research process

4. The research process
STAGE 1: DEFINING THE PROBLEM
1.Deciding on the research topic
2.Conducting a literature review
3.Specify a research question
4.Formulating a hypothesis
5.Operationalizing concepts

5. The research process
STAGE 2: Obtaining the information
1.Ethics
2.Research design
3.Sampling
4.Data collection
STAGE 3: Analysing and interpreting the information
1.Describing and interpreting quantitative data
2.Analyses and interpretation of qualitative data

6. The research process
STAGE 4: Communicating the results
1.Report

7. Qualitative data analysis
and interpretation

8. Outcomes
1.The purpose of qualitative data analysis
2.Data analysis in qualitative research process
3.Analysis and interpretation of qualitative data

9. Purpose of qualitative data
analysis
Qualitative research
1.Any type of research that produces findings not
arrived at by statistical procedures
2.Persons, lives, experiences, emotions
3.Qualitative data analysis – an inductive process of
organising data into categories / themes and
identifying patterns among them

10. When does one start with data
analysis in qualitative research?
1.Data analysis is an ongoing process that routinely starts prior to
the first interview
2.When the process of data collection begins, they start with
conducting interviews or observations
3.In practice ~ Data analysis tends to begin when data saturation
becomes noticeable
4.Data Saturation ~ Patterns & themes start to recur, and no new
information is added by more interviews.
5.At the end of data collection, data analysis starts to take all
information into account, taking on a more directed form.

11. How qualitative data are
analysed and interpreted
Steps, examples and pointers
1.There is no standard procedure for qualitative analysis, but
it does not mean that it is not systematic
2.A linear procedure is not followed
3.Occur in several cyclical, overlapping phases in which the
researcher moves back and forth between different levels
4.Researcher should identify the coding procedure to be
used to reduce the information to themes or categories

12. Step-wise plan for qualitative
data analysis
5. The collected data must be organised and prepared for
analysis
Transcribing the interview word-for-word,
Optically scanning material,
Typing field notes
Sorting and arranging the data into different types
depending on the sources of information

13. Step-wise plan for qualitative
data analysis
STEP 1:
After preparing and organizing the data, read through all the
transcriptions carefully. Make notes of ideas as they come to
mind
STEP 2:
Select one document (transcribed interview) – the most
interesting/shortest/ one on the top of the pile. Go through it
asking yourself: what is it about. Think of the underlying
meaning of the information. Write down your thoughts in the
margin.

14. Step-wise plan for qualitative
data analysis
STEP 3:
Make a list of all the topics. Put similar topics
together. Form these topics into columns that might
be grouped as “major topics, unique topics or
leftovers”

15. Step-wise plan for qualitative
data analysis
STEP 4:
1.Take the list of topics and assign to each topic an
identifiable code. Codes are:
~ Tags or labels assigned to meaning units.
~ Usually attached to chunks of varying sized words,
phrases, sentences or whole paragraphs
~ A shorthand method or way of identifying the
theme/category in a transcription.
~ Typically take the form of strings of letters and/symbols.

16. Step-wise plan for qualitative
data analysis
STEP 4:
Go back to your transcribed data and write the codes next
to the data segments that correspond with the codes
First-level / open coding or open coding – a combination of
identifying meaning units, fitting them into themes and
assigning code to the themes
Meaning unit – segments (or chunks) of information that are
the building blocks of a classification scheme

17. Step-wise plan for qualitative
data analysis
STEP 5:
Find the most descriptive wording for your topics and
turn them into themes/categories
STEP 6:
Make a final decision on the abbreviation for each
theme/category and put these codes

18. Step-wise plan for qualitative
data analysis
STEP 7:
Use the cut-and-paste method, assemble the data
material belonging to each theme/category in one
place and do a preliminary analysis
STEP 8:
If necessary, recode the existing data. If not, start on
interpreting and reporting your research findings.