The document provides a comprehensive overview of data analysis methods and best practices for conducting research, emphasizing the importance of planning and framing one's approach to analysis. It highlights the distinction between quantitative and qualitative research, offers tips for managing data, and stresses the critical role of the researcher's assumptions and methodologies. Specific guidance on interview analysis and techniques like thematic analysis is also presented, along with advice on maintaining ethical considerations throughout the research process.

1. RESEARCH METHODS
WORKSHOP
DATA ANALYSIS:
HINTS AND TIPS
25th May 2011
Katrina Pritchard

2. DATA ANALYSIS HINTS AND TIPS
This presentation:
Planning your approach to analysis
Getting started with data analysis
Specific hints and tips for analysing interviews
Questions?

3. PLANNING YOUR APPROACH TO ANALYSIS
What types of empirical research have been carried out in your area of
interest?
Does one type dominate? e.g. case studies? survey research?
READ empirical papers and particularly note limitations and issues raised.
Ensure you read BOTH quantitative and qualitative examples and get a
sense of how these differ with respect to your topic.
What techniques do YOU feel most comfortable using or have
experience with?
What is implied in the wording of your research question(s)?
e.g. how vs. how many
What actual data have you collected/are collecting?
PRIMARY DATA and/or SECONDARY DATA
QUANTITATIVE and/or QUALITATIVE DATA

4. PLANNING YOUR APPROACH TO ANALYSIS
All research is underpinned by a set of assumptions about
reality (ontological assumptions) and the way in which
reality can be known (epistemological assumptions).
Without going to far into the philosophical debate, you
should at the very least ask yourself:
What are my assumptions about the phenomena I am researching?
(e.g. a fixed characteristic or contextually dependent?)
What are my assumptions about the way in which I can best access
these phenomena? (e.g. it is waiting to be measured or is
constructed through the research?)
What is my role as a researcher in respect to this process? (e.g. what
impact to I have on these phenomena?)

5. PLANNING YOUR APPROACH TO ANALYSIS
There are no right or wrong answers but you should to
use this to frame both how you describe your
methodological position in your dissertation AND how
you approach analysis.
A common weakness in submitted dissertations is
inconsistency between the positioned claimed in the
methodology section and how the findings are then
presented – some switch positions several times in the
space of a few pages!

6. PLANNING YOUR APPROACH TO ANALYSIS
Quantitative Research Qualitative Research
Closed questions Open questions
Large samples Small samples
Researcher defined Emergent and holistic
variables focus
Controlled settings Natural Settings
Individual respondents Individual respondents
hidden visible
Statistical analysis Interpretative analysis
Fixed research design Fluid research design
Objective Subjective
BUT each of these categories contains a vast array of methods, be specific
about the ‘flavour’ you are using. For multi-method designs you need to
think carefully about the implications of tensions between your methods.

7. GETTING STARTED WITH DATA ANALYSIS
Set up a spread-sheet or word table to log and keep track
of your data
Don’t forget to included secondary data such as copies of
company reports or newsletters
If you are using pseudonyms or participant codes keep a master
list of how these relate to real names so you can track back if
needed
Work out what needs to be done (if anything) to transform
your data prior to analysis:
Download (e.g. Materials from websites)
Data processing (e.g. Entering questionnaire results)
Transcription (e.g. For recorded materials)
Translation

8. GETTING STARTED WITH DATA ANALYSIS
Set aside a note book or word document for recording your
thoughts and ideas as your analysis progresses
Make regular (secure) back ups of your data (and indeed
anything to do with your dissertation)
Know when your supervisor is available for support. Ideally
try and discuss your experience of the early stages of
analysis so that you can iron out any glitches asap.

9. GETTING STARTED WITH DATA ANALYSIS
Plan your overall approach but be prepared to play and test out
ideas:
Keep your research question(s) firmly in mind!
Go back to the literature and/or organizational context to check the
sense of your approach
Work out the difference between DESCRIBING your data and
ANALYSING it. A common weakness of submitted dissertations
is the lack of actual analysis.
For example: Seven people interviewed commented on the lack of
managerial support for training but everyone else felt they could
attend training when needed vs. There were conflicting views
expressed with respect to opportunities for training. Those who
commented on positive managerial support seem to suggest that
this was.......

10. SPECIFIC HINTS AND TIPS FOR ANALYSING INTERVIEWS
Analysing interviews means that you will need to:
work with, and make sense of, large volumes of
unstructured data
go beyond description to generate insight
weave a convincing story in respect to the research
question posed
critically appraise your own role in knowledge production

11. SPECIFIC HINTS AND TIPS FOR ANALYSING INTERVIEWS
Most common method applied at MSc level is template/thematic
analysis (see links posted on discussion board )
Be careful of “coding fetishism” and remember that “coding is the
first step to opening up meaning” not an end in itself
Lyn Richards, Handling Qualitative Data: A Practical Guide 2005 – highly
recommended, summary of notes posted on discussion board
For each theme write down: thoughts about it, issues, ideas, gaps,
relationships i.e. a summary of analysis and ideas in respect to each.
Use basic tools such as spreadsheets or word tables to enable
comparison across interviews and within accounts, such as below:
Joe Debbie Adam
Theme 1: My manager I am a lovely Joe is
Managers Debbie is Manager Debbie’s
lovely favourite

12. SPECIFIC HINTS AND TIPS FOR ANALYSING INTERVIEWS
You do not have to analyse everything – there will probably be
too much data
Avoid too much counting (three people said X vs. two people
said Y) unless you are deliberately adopting an analytic approach
of converting qualitative to quantitative data (usually done via
content analysis)
Think of interviews as a story told on a particular occasion rather
than a list of facts. Often areas of confusion or contradiction can
be analytically the most interesting so be very wary of classifying
particular statements as ‘true’ or ‘false’
Keep an eye on research ethics at all times (especially in terms of
what you are revealing in your write up)

13. SPECIFIC HINTS AND TIPS FOR ANALYSING INTERVIEWS
Going round in circles is a good thing ... but you might get
dizzy ... and you do need to know when to stop!
Data
Literature Themes
Findings Analysis

14. DATA ANALYSIS HINTS AND TIPS
Planning your approach to analysis
Getting Started with Data Analysis
Specific Hints and Tips for analysing interviews
Questions?

15. QUESTIONS?