Introduction to data analysis
In order to gain insight from data, it is necessary to carry out detailed analysis.
This important step should be closely aligned with the research design and should be appropriately planned at the outset of your research.
The type of analysis can be either a descriptive or an inferential analysis. Find out more from this short Lynda.com video, ‘Understanding descriptive and inferential statistics’.
This is an additional video, hosted on YouTube.
If for any reason you can’t view this video you can read the transcript for the ‘Understanding descriptive and inferential statistics’ video.
Often, quantitative research can be limited to a descriptive analysis, particularly if the number of participants is small for the more advanced inferential analysis (Creswell and Plano Clark 2017).
Some analytical approaches in research can test a relationship between variables. For instance, if the research question aims to establish if there is a relationship between two variables, a correlation or regression analysis will be more appropriate.
There are software packages specifically used for data analysis. These include the Statistical Package for Social Science (SPSS) and the NVivo, which are used for quantitative and qualitative research, respectively. These pieces of software can provide statistical, thematic and inferential analysis.
Investigate other types of analytical software. What did you find?
Which analytical technique do you think will be most suitable for analysing the information that you intend to collect?
Which software would be appropriate? How will you ensure that the results are valid and reliable?
Don’t forget to capture your thinking in your learning log or portfolio.
Creswell, J. W., and Plano Clark, V. L. (2017) Designing and Conducting Mixed Methods Research. 3rd edn. Thousand Oaks, CA: SAGE Publications
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