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Research methods workshop data analysis

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A presentation on data analysis (with specific focus on analysing interviews) for MSc HRD and consultancy students at Birkbeck.

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Research methods workshop data analysis

  1. 1. RESEARCH METHODSWORKSHOPDATA ANALYSIS:HINTS AND TIPS25th May 2011Katrina Pritchard
  2. 2. DATA ANALYSIS HINTS AND TIPSThis presentation: Planning your approach to analysis Getting started with data analysis Specific hints and tips for analysing interviews Questions?
  3. 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. 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. 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. 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 SubjectiveBUT each of these categories contains a vast array of methods, be specificabout the ‘flavour’ you are using. For multi-method designs you need tothink carefully about the implications of tensions between your methods.
  7. 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. 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. 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. 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. 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. 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. 13. SPECIFIC HINTS AND TIPS FOR ANALYSING INTERVIEWSGoing round in circles is a good thing ... but you might getdizzy ... and you do need to know when to stop! Data Literature Themes Findings Analysis
  14. 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. 15. QUESTIONS?

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