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Surviving and Thriving in Postgraduate Research pp 921–1002Cite as

How Should I Approach Data Analysis and Display of Results?

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Abstract

The basic goal of all forms of data analysis is to build meaning from the raw data and convey that meaning to one or more specific audiences. This chapter reviews approaches to data analysis which provide key pathways for telling the stories about what you have learned through your research journey by helping readers/users connect evidence, including strategic data displays, with those stories. Quantitative analysis deals with data in the form of numbers, measurements and indices whereas qualitative analysis deals with data that are in non-numerical form, which can include recordings, documents and transcripts, images, websites and films/videos. For certain purposes, via the Transformative data-shaping strategy, qualitative data may be transformed (i.e., ‘quantitised’) into a quantitative form prior to analysis, e.g., participants, words and codes can be categorised, counted, ranked or rated, yielding quantitative data. Equally, quantitative measurements can be ‘qualitised’ such that richer interpretive meaning is attached to the numbers. No matter what type of data you have gathered, analysis will almost always transform, condense, aggregate, re-represent, thematise or categorise the raw data to build meaning.

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Authors and Affiliations

  1. UNE Business School, University of New England, Armidale, NSW, Australia

    Ray Cooksey

  2. RMIT University Vietnam, Ho Chi Minh City, Vietnam

    Gael McDonald

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  1. Ray Cooksey
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  2. Gael McDonald
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Correspondence to Ray Cooksey .

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Cooksey, R., McDonald, G. (2019). How Should I Approach Data Analysis and Display of Results?. In: Surviving and Thriving in Postgraduate Research. Springer, Singapore. https://doi.org/10.1007/978-981-13-7747-1_21

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  • DOI: https://doi.org/10.1007/978-981-13-7747-1_21

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