This document provides an overview of qualitative data analysis techniques including inductive and deductive approaches, coding methods like open coding and axial coding, developing code hierarchies, comparative analysis using tables and models, and ensuring analytic quality through reflexivity. It discusses writing as a tool for analysis, such as keeping a research diary, and the importance of anonymity and validity in qualitative research ethics.

1. Analysing
Qualitative Data

2. Introduction to Qualitative Analysis
Writing as a Tool in Analysis
Thematic Coding and Categorising
Comparative Analysis
Analytic Quality and Ethics

3. Introduction to Qualitative Analysis

4. What is going on here?

5. • Inductive approach
• Generalisation and justification of an explanation
based on accumulation of lots of particular. but
similar, circumstances.
• Deductive approach
• A particular situation is explained by deduction from
a general statement about the circumstances.
Dealing with General Statements

6. • Nomothetic approach
• What do specific people, events and settings have in
common?
• Idiographic approach
• Every individual is a unique case. Focus is on the
factors that may be individual to that one case
Dealing with Unique Outcomes

7. • Realism approach
• There is a world with objects and people that exist.
This can include aspects such as clowns, atoms,
learning styles…
• Idealism approach
• We can’t know anything about a real world and
instead experience it through constructs and ideas.
Dealing with World Reality

8. Basically…lots of people
think lots of things in lots
of different ways.

9. Writing as a Tool in Analysis

10. Write Early and Write Often!
• The more you write the easier it gets
• If you write a little bit every day, it becomes a habit
• Tiny bits of writing add up to a lot of writing
• The longer you leave it unwritten the worse the task
becomes.

11. Don’t get it right, get it written!
• Until it is on paper, no-one can help you get it right
• Drafting is a vital stage in clarifying thought
• Start writing the bit that is clearest in your head
• Drafting reveals the places where it isn’t right (yet!)

12. Research Diary
Can be an open document or a very personal
thing, really up to you.
• What you did, and where, how and why
you did it.
• What you have been reading
• Contact summaries about what people,
events or situations were involved
• What data you collected
• Particular achievements, dead ends and
surprises
• Thoughts that come into your mind
about what has been happening

13. Field Notes
Notes taken whilst in the research setting. Used a
lot in ethnographic work.
• Not planned or structured. Are normally
open ended, loose, and messy
• Can be used to represent an event, or to
give an account of it. Identify aspects
which are significant
• Descriptions of what people said and
did, but not a simple recording of facts

14. Memos
A way to theorise and comment on your ideas as
you carry out analysis and also in the lead up to
this
• Are notes to yourself or to others in the
research team
• Can be organised into different
categories to make it easy to
understand…

15. ON MN TN PN
Observational Notes
Methodological Notes
Personal Notes
Theoretical Notes

16. • A new idea for a code: Might be sparked
by something that a respondent says.
Keep all of these close for cross-
referencing
• A quick hunch: Support this with some
evidence in your data
• Integrative discussion: Brings together
one or more memos
• Dialogue among researchers: Sharing
ideas with others
• To question quality of data:
Respondent wasn’t entirely open or
were not qualified to talk about issue

17. • Question the original analytic
framework: Memo against an existing
code to raise questions about whether
they make sense
• Puzzling or surprising issues: Spot
what is surprising, harder than you
would think!
• Alternative to other memos: Internal
dialogue - what are the other options?
• No clear idea: Writing things down can
help to flesh out a bigger idea
• Raise a general theme: bring issues
together

18. The Final Report
Bringing everything together with all the writing
that has been completed so far.
• Layout and purpose is down to the
situation that it is being created for
• Have an organised structure to tell the
story of the data you have collected
• The first time you write it won’t be the
last time you read it. Be prepared to
redraft…

19. The Final Report
Redrafting • Read through and ask yourself:
• What am I trying to say?
• Who is the text for?
• What changes will make the text
clearer
• Big changes you might consider:
• Reordering parts of txt
• Adding examples
• Deleting parts that are confusing
• Minor changes include:
• Simpler wording
• Shorter sentences
• Shorter paragraphs

20. academic phrasebank

22. Thematic Coding and Categorising

23. Coding is how you define what the data you are analysing
are about. It involves identifying and recording one ore
more passages of text or other data items that exemplify
the same theoretical or descriptive idea.

24. • Text can be retrieved that has been coded in the same
way to show examples of the same phenomenon, idea, or
activity. This lets you look at the data in a more
structured way
• Lists of codes, when developed into a hierarchy, can be
used to further examine questions and relationships
between ideas.

25. Defining Your Codes
Give your codes descriptive names, and define
how it should be applied. Keep this in a document
and include?
• Label or name of the code
• Who coded it
• Date of the code and if it has been
changed
• Definition of the code - description of
analytical idea
• Any other notes that you think may be
useful.

26. Mechanisms of Coding
• What is going on?
• What are people doing?
• What is the person saying?

27. What can be coded?
1. Specific acts, behaviours - what people say or do.
2. Events - these are usually brief, one-off events or
things that someone has done
3. Activities - longer duration than acts and often
take place in a particular setting with several
people
4. Strategies, practices, or tactics - activities aimed
towards some goal

28. What can be coded?
5. States - general conditions experienced by people
for found in organisations
6. Meanings - a wide range of meanings can be
taken, this can direct participants actions
7. Participation - peoples involvement or adaption
to a setting
8. Relationships or interactions - between people,
considered simultaneously.

29. What can be coded?
9. Conditions or constraints - the precursor to
or cause of events or actions
10. Consequences - what happens if…
11. Setting - the entire context of the events
under study
12. Reflective - researchers role in the process

30. Grounded Theory
• Focus on generating novel ideas from the
data opposed to testing the theories
specified beforehand
• Coding divided into three stages
• Open Coding
• Axial Coding
• Selective Coding

31. Grounded Theory
• Examine the text by making comparisons and asking questions
• Avoid labels that merely describe a section of text
• Formulate theoretical or analytical codes
Open Coding
• Bring out what is distinctive about the text and its content
• Thing about comparisons al the time when you are coding
Constant Comparison

32. Grounded Theory
Constant Comparison
Analysis of word
phrase or sentence
Flip-Flop
Technique
Systematic
Comparison

33. Grounded Theory
Constant Comparison
Far Out
Comparisons
Waving the Red
Flag

37. Comparative Analysis

38. Rearranging codes into a hierarchy involves
thinking about what kinds of things are
being coded and what questions are being
answered.

39. Branches can be divided into sub-branches
to indicate different sort of things

40. • Keeps Things Tidy
• As analysis proceeds you will develop a large number
of codes
• Long lists of repeating codes are not helpful
• Can constitute an analysis of the data itself
• Can understand respondents’ view of the world
• Prevents the duplication of codes
• Especially true when you have high numbers of
codes that you are working with
Functions of the Code Hierarchy

41. • Helps see the range of things
• Codes can have dimensions, this helps to uncover
what they can be
• Makes it easier to do some types of analytics
• When people do X do they also do Y
Functions of the Code Hierarchy

42. Coding provides the shorthand synthesis
for making comparisons between
1. Different people, objects, scenes, or
events
2. Data from the same people, scenes,
objects or events
3. Incidents with incidents

43. Female Male
Routine
My routine’s determined by child care
requirements (Pauline). I get the paper every day
without fail (Mary). I used to go down to the Job
Centre a lot, I kept a file of all the letters I
received (Sharon
I used to spend mornings going through the
papers. I ether used to buy papers or go down
to the library. Afternoons writing off to places for
information or filling in application forms, and
then events for the even gin papers, again (Jim).
Just the same pattern all through the week
(Harry)
Haphazard
Not really, I just do it. It happens (susan) Not
really, because my husband works shift work
(Mary)
No routine, but I keep myself busy. I’ve plenty of
gardening to do (Dave). No, not really. I usually
go down and have a loo Monday, Wednesday,
Friday, something like that (Andy)
Entrepreneurial
Personal approaches to firms and through
friends (Mary)
I…spend…a couple of days every week with a
company.. I make sure tha tthey know that I’m
there (John)

44. A common use for tables it to enable you to
carry out a case-by-case comparison. One
key outcome of this can be the creation of a
typology of cases based on two or more
coding ideas.

45. Using a Model to Describe a Phenomenon
A model is a framework that attempts to
explain what has been identified as key
aspects of a phenomenon being studied in
terms of a number of different aspects.

46. Axial Coding Model
Causal Conditions
Phenomenon
Strategies
Context
Intervening Conditions
Action/Interaction
Consequences

47. Axial Coding Model
Causal Conditions
Phenomenon
Strategies
Context
Intervening Conditions
Action/Interaction
Consequences Get a home, prison, hospital
Becoming homeless, surviving without a home
Stay with friends, live rough, seek help from agencies
Hostels for homeless, street culture, temporary accommodation
Drugs, criminal record, desire to be independent
Personal contacts, friendship networks, drug treatment, charities,
begging, petty crime, move to new area
Example from Study on Homelessness
Job Loss, debt, drug problems, sexual identity

48. Analytic Quality and Ethics

49. Traditional Approaches to Quality
• Valid
• If the explanations are really true or accurate and correctly
capture what is actually happening
• Reliable
• If the results are consistent across repeated investigations
in different circumstances with different investigators
• Generalsable
• True for a wide (but specified) range of circumstances
beyond those studied in the particular research

50. Reflexivity

51. We are encouraged to be reflexive in our
account of the research process, the
data collected and the way we write up.
Reflexivity shows the partial nature of
our representations of reality and the
multiplicity of competing versions of
reality

52. • Examine the wider relevance of your project and its setting, and
the grounds on which empirical generalisations are made.
• Discuss the features of your project and its setting that are left
un-researched. Why did you make these choices and what
implications for the research findings happen because of this?
• Be explicit about the theoretical framework you are operating
within, and the broader values and commitments you bring to
your work
Reflexive Good Practice

53. • Critically assess your integrity as a researcher by considering:
• the grounds on which knowledge claims are being justified
(length of the fieldwork, extent of trust and report
developed)
• your background and experiences in the setting and topic
• the strengths and weaknesses of your research design and
strategy
Reflexive Good Practice

54. • Critically assess the data by
• discussing the problems that arose during all stages of the
research
• outlining the grounds on which you developed the
categorisation system used to interpret the data, identifying
clearly whether this is one used by respondents them selves,
or an analyst constructed one
• discussing rival explanations and alternative ways of
organising the data
• providing sufficient data extracts in the text to allow readers
to evaluate the inferences dawn and the interpretations
made
Reflexive Good Practice

55. • Show the complexity of the data, avoiding the suggestion that
there is a simple fit between the situation and your
representation of it by:
• discussing negative cases that fall outside the general
patterns and categories employed to structure your analysis
• showing the multiple and often contradictory descriptions
given by the respondents themselves
• stressing the contextual nature of respondents accounts and
descriptions
Reflexive Good Practice

56. Data Validity
Triangulation Respondent
Validation
Constant
Comparison
Evidence

57. The key to ethics is to balance the harm
(even minimal) that research might do
against its benefits. Qualitative data is
so detailed, there is always a danger
that confidentiality may be breached, so
anonymous information is especially
important.

58. Introduction to Qualitative Analysis
Writing as a Tool in Analysis
Thematic Coding and Categorising
Comparative Analysis
Analytic Quality and Ethics

59. Information in this
presentation was
based on…