Lecture 10: From data analysis to reporting Flashcards
1
Q
Reduction of data depends on three things
A
- What data do you have
- What is research perspective that you take
- What are your objectives
2
Q
How to do data reduction
A
- labelling
- causal analysis
- matrix
3
Q
Content analysis
A
Making interferences about data by systematically identifying special characteristics within them
4
Q
Characteristics, content analysis
A
- common classes=everyday categoreis
- special classes=specialist categories
- theoretical classes=arise in process of analysis
5
Q
Secondary analysis
A
Integration of core categories into theory
steps:
- finding a storyline around core categoreis
- validate relationships between categories against data
- re-iterate
6
Q
Moments of analysis
A
- Devising frameworks, interview guide
- Interview themselves
- Desk analysis afterwards
7
Q
Member check
A
It is a preliminary analysis of interview
Integrate interpretation
Done after coding and done some analysis
8
Q
2 starting points for data analysis
A
- procedures
x coding
x indexing
x categorising - creativity
x interpreting
x exploring relations
9
Q
What is data analysis and two ways to do it
A
Actively working with data
- reduction
- complication: by looking for patterns at higher levels of abstraction
