Lecture 10: From data analysis to reporting Flashcards

1
Q

Reduction of data depends on three things

A
  1. What data do you have
  2. What is research perspective that you take
  3. What are your objectives
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2
Q

How to do data reduction

A
  • labelling
  • causal analysis
  • matrix
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3
Q

Content analysis

A

Making interferences about data by systematically identifying special characteristics within them

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4
Q

Characteristics, content analysis

A
  • common classes=everyday categoreis
  • special classes=specialist categories
  • theoretical classes=arise in process of analysis
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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

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6
Q

Moments of analysis

A
  • Devising frameworks, interview guide
  • Interview themselves
  • Desk analysis afterwards
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7
Q

Member check

A

It is a preliminary analysis of interview
Integrate interpretation
Done after coding and done some analysis

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8
Q

2 starting points for data analysis

A
  • procedures
    x coding
    x indexing
    x categorising
  • creativity
    x interpreting
    x exploring relations
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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

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