Lecture Slides
Video Lecture (from 2019)
Concepts
Qualitative data
Basic Tools
Thematic analysis
Open coding
Axial coding
Selective coding
Codebook
Analytic memo
Saturation
Writing up
Advanced Tools
Inductive theorising
Deductive theorising
Analytic comparison
Narrative & sequence analysis
Opening Stories
Story 2: Students who did qualitative and quantitative projects
In early years of teaching this course, students could pick whether they did EITHER qualitative OR quantitative data collection and analysis.
Only about 20% of quantitative studies found what they thought they would find. BUT about 80-90% of qualitative studies found what they thought they would find.
Why? Easier to fool yourself with qualitative data.
Solution? You need to be skeptical, logical, and really test one another to make sure the evidence says what you think it says.
Why learn qualitative analysis?
There is a huge amount of qualitative data in the world
- Newspaper articles, in depth interviews, archival records, field notes, pictures and art, TV shows, Shakespeare’s plays, and more.
Not immediately obvious how we can systematically analyse this
- We can’t use maths and stats
One main method - thematic analysis - and you need to use it for projects.