21890 Chap.7 Case Research and Secondary Data Analysis
Case Research and Secondary Data Analysis
Case research
A case study investigates a contemporary phenomenon in depth and in its real-life context, drawing on many sources of evidence.
With limited time, fewer cases allow deeper analysis, provided each case has enough secondary data.
Four analysis approaches
Re-analysis confirms original findings, supplementary analysis explores parts the original left open, supra analysis pursues new aims, and amplified analysis compares qualitative data sets.
Before you interpret
Check for collection errors, whether you hold raw data or someone's interpretation, and whether period, people, variables and units fit your question.
Then analyse by theme, quantitatively or qualitatively.
What this chapter covers
- 01
Case research defined
- 02
How many cases to study
- 03
Re-analysis and supplementary analysis
- 04
Supra and amplified analysis
- 05
Applicability checks
- 06
Quantitative and qualitative analysis
Worked example · free
Decide how many cases fit a 60-hour analysis budget
- 1Hours per case equal 60 divided by the number of cases.
- 1At 3 cases each receives 20 hours, which meets the minimum; at 4 cases each receives 15 hours, which falls short.
- 1So the study can include at most 3 cases, and a fourth would cut every case from 20 to 15 hours.
Key terms
- Supra Analysis
- Secondary analysis whose aims go beyond those of the study that collected the data.
- Amplified Analysis
- Secondary analysis that sets several qualitative data sets side by side.
- Thematic Analysis
- Qualitative analysis that identifies and interprets recurring ideas across texts or other material.
Case Research and Secondary Data Analysis FAQ
How many cases should my project include?
The Week 5 lecture's guidance starts from your resources: each case you leave out frees time for more depth in the rest. More cases help comparison but thin the evidence per case, so choose the number your time and the available secondary data can support.
What is the difference between re-analysis and supra analysis?
Re-analysis re-examines a previous study's data to confirm or validate its findings, keeping the original aims. Supra analysis uses existing data for aims that go beyond the original study, which is common when your question was never asked by the people who collected the data.
Can qualitative methods be used with secondary data?
Yes. The Week 1 lecture states that both qualitative and quantitative approaches can be used to analyse secondary data. Published reports, minutes and interview transcripts suit thematic analysis, while statistics and census tables suit quantitative analysis.
Why is case research useful for this project?
The Week 5 lecture explains that a case lets you study a phenomenon where it actually happens, that why, what and how questions can be answered with a full understanding of a complex phenomenon, and that cases suit early exploratory work when the variables are still unknown.
What should I check before interpreting someone else's data?
Look for errors from poor collection or sampling, check whether you can verify the method's rigour, and ask whether you hold raw data or another person's interpretation. Then confirm that the period, people, variables and units all fit your question.
What is supplementary analysis?
It takes a more in-depth look at emergent issues or parts of a data set that the original study did not explore. A student using regional tables from a national survey that its authors never discussed would be carrying out supplementary analysis.
How should the analysis section of the report be organised?
The Assessment 3 guidelines ask for the critical analysis and discussion section to be structured around themes derived from your literature review, with critical writing that weighs perspectives and synthesis that integrates what different authors say about the same topic.
Assessment move
Name your analysis approach and say why it fits in one sentence for your method section. Run the lecture's applicability checks on each data set, especially units and comparability, and keep a note of how you handled any mismatch. Plan your analysis headings as themes, not sources.
If you study more than one case, make sure each has enough published material before you commit, and decide in advance which comparisons you will make. For each data set, write down whether you have raw figures or someone's summary, because that decides which analysis approach you can honestly claim in your method section.
Working through Case Research and Secondary Data Analysis in 21890? Sia is AskSia’s AI Management tutor — ask any 21890 Case Research and Secondary Data Analysis question and get a clear, step-by-step explanation grounded in how 21890 is taught and assessed. Read this chapter free, then take your hardest questions to Sia.