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Data Management and Analysis

Data Management and Analysis. What in the world am I going to do with all this data?. Reflective Analysis. While computer programs can facilitate analysis, it is the researcher who needs to strategically, creatively, and intuitively analyse their data.

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Data Management and Analysis

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  1. Data Management and Analysis What in the world am I going to do with all this data? O'Leary, Z. (2004) The Essential Guide to Doing Research. London: Sage Chapter Twelve

  2. Reflective Analysis • While computer programs can facilitate analysis, it is the researcher who needs to strategically, creatively, and intuitively analyse their data O'Leary, Z. (2004) The Essential Guide to Doing Research. London: Sage Chapter Twelve

  3. Keeping an overall sense of the project • Analysis should be approached as a critical, reflexive, and iterative process that cycles between data and an overarching research framework • It is crucial for researchers to keep a keen sense of the overall project and think their way through analysis O'Leary, Z. (2004) The Essential Guide to Doing Research. London: Sage Chapter Twelve

  4. Managing the Data • Managing data involves: • familiarizing yourself with appropriate software • developing a data management system • systematically organizing the data • conducting a preliminary screening • and entering the data into a computer program O'Leary, Z. (2004) The Essential Guide to Doing Research. London: Sage Chapter Twelve

  5. Crunching the Numbers • Being able to do statistics no longer means being able to work with formula • It is much more important for student researchers to be familiar with the language and logic of statistics, and be competent in the use of statistical software O'Leary, Z. (2004) The Essential Guide to Doing Research. London: Sage Chapter Twelve

  6. Data Types • Different data types demand discrete treatment, so it’s important to be able to distinguish variables by: • cause and effect (dependent or independent) • and measurement scales (nominal, ordinal, interval, and ratio) O'Leary, Z. (2004) The Essential Guide to Doing Research. London: Sage Chapter Twelve

  7. Descriptive Statistics • Descriptive statistics are used to summarize the basic feature of a data: • measures of central tendency (mode, median, and mean) • dispersion (range, quartiles, variance, and standard deviation) • and distribution (skewness and kurtosis) O'Leary, Z. (2004) The Essential Guide to Doing Research. London: Sage Chapter Twelve

  8. Shape of the Data O'Leary, Z. (2004) The Essential Guide to Doing Research. London: Sage Chapter Twelve

  9. Inferential Statistics • Inferential statistics allow researchers to assess their ability to draw conclusions that extend beyond the immediate data, i.e.) • if a sample represents the population • if there are differences between two or more groups • if there are changes over time • or if there is a relationship between two or more variables O'Leary, Z. (2004) The Essential Guide to Doing Research. London: Sage Chapter Twelve

  10. Selecting the right statistical test • Selecting the right statistical test relies on knowing: • the nature of your variables • their scale of measurement • their distribution shape • and the types of question you want to ask O'Leary, Z. (2004) The Essential Guide to Doing Research. London: Sage Chapter Twelve

  11. Working with Words • In qualitative data analysis, there is a common reliance on words and images to draw out rich meaning • But there is an amazing array of perspectives on the precise focus of, and techniques for, conducting analysis O'Leary, Z. (2004) The Essential Guide to Doing Research. London: Sage Chapter Twelve

  12. Logic and Methods • The methods and logic of qualitative data analysis involve: • uncovering and discovering themes that run through the raw data • and interpreting the implication of those themes for research questions O'Leary, Z. (2004) The Essential Guide to Doing Research. London: Sage Chapter Twelve

  13. Funnelling Towards Meaning O'Leary, Z. (2004) The Essential Guide to Doing Research. London: Sage Chapter Twelve

  14. Cycles of Reasoning • Qualitative data analysis often involves: • moving through cycles of inductive and deductive reasoning • thematic exploration (based on word, concepts, literary devices, and nonverbal cues) • and exploration of the interconnections among themes O'Leary, Z. (2004) The Essential Guide to Doing Research. London: Sage Chapter Twelve

  15. Qualitative Data Analysis Strategies • There are a number of paradigm/discipline based strategies for qualitative data analysis including: • overarching methodologies • content, discourse, narrative, and conversation analysis • semiotics • hermeneutics • and grounded theory O'Leary, Z. (2004) The Essential Guide to Doing Research. London: Sage Chapter Twelve

  16. Drawing Conclusions • Your findings and conclusions need to flow from analysis and show clear relevance to your overall project • Findings should be considered in light of: • significance • current research literature • limitations of the study • and finally your questions, aims, objectives, and theory O'Leary, Z. (2004) The Essential Guide to Doing Research. London: Sage Chapter Twelve

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