This document provides an overview of several qualitative and quantitative research methods and analysis techniques. It discusses interpretative phenomenological analysis (IPA) for qualitative analysis, which aims to explore participants' experiences and perspectives while acknowledging the researcher's own biases. It also reviews grounded theory methodology, discourse analysis techniques, and narrative analysis approaches. For quantitative analysis, it outlines organizing data, visual presentation methods, measures of central tendency, measures of variation, and common statistical tests. The document presents steps and considerations for applying these diverse analytical methods to research.

1. ANALYSIS OF
DATA
QUALITATIVE AND
QUANTITATIVE METHODS

2. QUALITATIVE ANALYSIS

3. INTERPRETATIVE
PHENOMENOLOGICA
L ANALYSIS
IPA

5. • PHENOMENOLOGY: IMPOSSIBILITY OF
GAINING DIRECT ACCESS TO RESEARCH
• PARTICIPANTS’ LIFE WORLDS
• AIM IS TO EXPLORE THE PARTICIPANT’S
EXPERIENCE/PERCEPTION OF THE WORLD
FROM HIS OR HER PERSPECTIVE;

6. • INTERPRETATION: IMPLICATION OF THE
RESEARCHER’S OWN VIEW OF THE
WORLD
• THE ATTEMPT TO REPORT ON THE
PARTICIPANT’S EXPERIENCE WILL
INEVITABLY BE DISTORTED (BIASED)
BY THE PHENOMENOLOGY OF THE
RESEARCHER

7. METHODOLOGY
• DATA COLLECTION
• PURPOSIVE HOMOGENOUS SAMPLING:
RECRUITING PARTICIPANTS WHO HAVE
EXPERIENCED THE PHENOMENON UNDER
INVESTIGATION, E.G. SUFFERING FROM
POST TRAUMATIC STRESS OR HAVING BEEN
BULLIED (NOT RANDOM SAMPLING …)
• FLEXIBLE INTERVIEW SCHEDULE: SEMI
STRUCTURED INTERVIEWS. CONSTRUCTING
AN INTERVIEW SCHEDULE.

8. • ANALYSIS
• IDENTIFICATION OF THEMES IN THE FIRST
CASE
• SEARCH FOR CONNECTIONS BETWEEN
THEMES (‘CLUSTERS’)
• MOVE ACROSS THE CASE WITH THE AIM
TO ESTABLISH SUBORDINATE THEMES
• INTEGRATION OF CASES: IDENTIFICATION
OF ‘MASTER THEMES’

9. CODING

10. CODING

14. GROUNDED THEORY
•INDUCTIVE PROCESS OF GENERATING
THEORY FROM DATA
•NO PRIOR ASSUMPTIONS
•RESEARCHER DETECT PATTERNS IN THEIR
OBSERVATION AND THEN CREATE
WORKING HYPOTHESIS THAT LEAD THE
PROGRESSION OF INQUIRY

15. 1.DATA
GATHERIN
G
2.CODIFICAT
ION AND
CATEGORIZ
ATION
6.REVIEW
OF
LITERATUR
E
5.THEORETI
CAL
FORMULATI
ON
3.MEMO
S
4.CLASSIFICATI
ON
STAGES OF
GROUNDED
THEORY

16. DISCOURSE ANALYSIS

17. WHAT IS “DISCOURSE”?
• DISCOURSE IS:
• LANGUAGE ABOVE THE SENTENCE OR ABOVE THE
CLAUSE
• A CONTINUOUS STRETCH OF SPOKEN LANGUAGE
LARGER THAN A SENTENCE, OFTEN CONSTITUTING
A COHERENT UNIT
• A STRETCH OF LANGUAGE PERCEIVED TO BE
MEANINGFUL UNIFIED, AND PURPOSIVE; LANGUAGE
IN USE
• (VIEWED) AS SOCIAL PRACTICE DETERMINED BY
SOCIAL STRUCTURES

18. RECENT APPROACH TO DA
• DISCOURSE IS NO LONGER STUDIES FOR
ITS OWN SAKE. DISCOURSE IS VIEWED AS A
SOCIAL PRACTICE.
• M. FOUCAULT, N. FAIRCLOUGH
• FOUCAULDIAN DISCOURSE ANALYSIS

19. •DISCOURSE IS CHARACTERISED
AS:
 PRODUCED/CONSUMED/MONITO
RED BY SOCIAL ACTORS
(PRODUCERS/RECEIVERS OF
SOCIAL PRACTICES);
SHAPED BY SOCIAL
STRUCTURES;

20. AUSTIN’S SPEECH ACT THEORY
• ARGUES THAT TRUTH CONDITIONS ARE
NOT CENTRAL TO LANGUAGE
UNDERSTANDING. UTTERANCES DO NOT
ONLY SAY THINGS, THEY DO THINGS.

21. WITH SOCIAL IMPLICATIONS;
SOCIALLY VALUED AND
REGULATED (PRODUCTION,
RECEPTION AND CIRCULATION).

22. DISCOURSE ANALYSIS
STEPS.DOCX

23. HOW TO DO A DISCOURSE
ANALYSIS

24. A. THINGS TO LOOK FOR
WHAT TO NOTICE WHEN DOING A DISCOURSE
ANALYSIS

25. 1. HIDDEN RELATIONS OF POWER
PRESENT IN THE ARTICLES
2. WHO IS EXERCISING THE
POWER, THAT IS, WHOSE
DISCOURSES ARE BEING
PRESENTED.

26. 3. WHO ARE CONSULTED FOR THE
ARTICLE (WHO ARE THE
SPOKESPEOPLE).
4. WHO IS THE ‘IDEAL SUBJECT’
OR AUDIENCE FOR THE ARTICLE.
5. WHAT IS LEFT UNSPECIFIED OR
UNSAID.

27. B. ASK THESE
QUESTIONS:
WHEN DOING A DISCOURSE ANALYSIS

28. 1. WOULD ALTERNATIVE WORDING
OF THE SAME INFORMATION
HAVE RESULTED IN A DIFFERENT
DISCOURSE BEING PRIVILEGED?
2. HOW ARE THE EVENTS
PRESENTED?
3. HOW ARE PEOPLE IN THE
ARTICLE CHARACTERISED?

29. 4. WHAT MESSAGE DOES THE
AUTHOR INTEND YOU TO GET FROM
THE ARTICLE?
5. WHY WAS THIS PARTICULAR
PICTURE CHOSEN TO ACCOMPANY
THE ARTICLE (IF APPLICABLE)?
6. WHAT REPETITION EXISTS (A)
WITHIN THE ARTICLE AND (B)
BETWEEN DIFFERENT ARTICLES ON
THE SAME TOPIC?

30. 7. WHAT PROFESSIONAL MEDIA
PRACTICES ASSIST WITH THE
PRESENTATION OF DOMINANT
DISCOURSES (EG EDITORIAL
CONSTRAINTS, JOURNALISTIC
STANDARDS ETC)?

31. NARRATIVE ANALYSIS

32. STEP-BY-STEP APPROACH TO
NARRATIVE ANALYSIS
• DECEPTIVELY SIMPLE SUMMARY OF AN APPROACH BORROWED FROM
DOUGLAS EZZY’S 2002 BOOK, QUALITATIVE ANALYSIS:
• 1. COMPILE THE STORIES
2. ANALYZE THE CONTENT, THE DISCOURSE, AND THE
CONTEXT OF EACH STORY, FOCUSING ON INSIGHTS
AND UNDERSTANDINGS
3. COMPARE AND CONTRAST STORIES FOR
SIMILARITIES AND DIFFERENCES IN CONTENT, STYLE,
AND INTERPRETATION

33. • 4. CONSIDER THE EFFECTS OF
BACKGROUND VARIABLES (IE:GENDER,
AGE)
5. IDENTIFY STORIES OR CONTENT THAT
ILLUSTRATE YOUR THEMES, INSIGHTS,
AND UNDERSTANDINGS.

34. Educational Research 2e:
Creswell
STEPS IN NARRATIVE RESEARCH
Identify a phenomenon
that addresses
an educational problem
Purposefully select an
individual to learn
about the phenomenon
Write a story about the
participant’s personal
and social experiences
Validate the accuracy of
the report
Collaborate with
participant storyteller in
all phases of research
Restory or retell
The individual’s
storyCollect stories from
the individual that
Reflect personal experience
Have them
Tell story
Collect other
Field texts
Build in past,
Present, future
Build in place
or setting
Describe their
story
Analyze story
for
themes

35. QUANTITATIVE ANALYSIS

36. STAGES

37. ORGANIZING DATA
• FREQUENCY DISTRIBUTION
• SCALES OF MEASUREMENT

38. VISUAL PRESENTATION OF
DATA
• BAR GRAPH (COLUMN CHART,
HISTOGRAM): BEST WITH FEWER
CATEGORIES
• PIE CHART: GOOD FOR DISPLAYING
PERCENTAGES; EASILY UNDERSTOOD
BY GENERAL AUDIENCE
• LINE GRAPH: GOOD FOR NUMERICAL
VARIABLES WITH MANY VALUES OR

39. data
Are our inferences valid?…Best we can do is to calculate probability
about inferences

40. Inferential Statistics
When making comparisons
btw 2 sample means there are 2
possibilities
Null hypothesis is true
Null hypothesis is false
Not reject the Null Hypothesis
Reject the Null hypothesis

41. MEASURES OF CENTRAL
TENDENCY
 MEAN
 MEDIAN
 MODE

42. ARITHMETIC MEAN
•“THE SUM OF THE TOTAL OF THE
OBSERVATIONS DIVIDED BY THE
NUMBER OF ITEMS OBSERVED”

43. MEDIAN
•“MEDIAN IS THE MIDDLE ITEM OF A
SERIES IF ALL THE ITEMS ARE
PLACED IN AN ARRAYED ORDER”

44. MODE
•THE SIZE OF THE VARIABLE AT
WHICH THE FREQUENCY IS MOST
CONCENTRATED OR OCCURS MOST
FREQUENTLY”

45. MEASURES OF VARIATION

46. MEASURES OF VARIATION
• SAMPLE RANGE
• SAMPLE VARIANCE
• SAMPLE STANDARD DEVIATION
• SAMPLE INTERQUARTILE
RANGE

47. SAMPLE RANGE
R = LARGEST OBS. -
SMALLEST OBS.
or, equivalently
R = xmax - xmin

48. SAMPLE VARIANCE
 
s
x x
n
i
i
n
2
2
1
1






49. SAMPLE STANDARD
DEVIATION
 
s s
x x
n
i
i
n
 



2
2
1
1

50. SAMPLE INTERQUARTILE
RANGE
IQR = THIRD QUARTILE - FIRST
QUARTILE
or, equivalently
IQR = Q3 - Q1

51. STATISTICAL TESTS
• PARAMETRIC AND NON PARAMETRIC
TESTS