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07/20 - Data Analysis and Interpretation by Mind Map: 07/20 - Data Analysis
and Interpretation
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07/20 - Data Analysis and Interpretation

Qualitative Analysis

Things to do

Finding categories and making connetions

Combining the evidence

Looking for themes and patterns

looking at the type of language used

Analysing Data

1. familiarise yourself with data

Read through it and start noting themes

Examples of reoccuring themes, Attitudes, Behaviours, Motivations, Views/opinions

Patterns, Frequencies, Magnitudes, Major occurences, Structures, Topics outlining, Processes, Causes, Consequences

2. Categories the data

Devise a conceptual framework/index

List themes, Journal, Post-it notes

Identify links or connections

Aim is to create sub-themes of concepts within larger categories, It's worth having an "other" category for themes that don't fit.

CODE and DEFINE categories

3. Code the data

Place an index next to the data

4. Sort the data

Focus on categories so you can look at the detail of each category

Thematic sets

5. Summarise and synthesis the data

Reduce the data and highlight relationships

Suggestions

Use POLTS as a theory led analysis

To improve teaching practice

Data

Types of Data

Ordinal Data, Data in order, eg. Unsatisfactory - Excellent

Nominal Data, eg. Male/Female, Used to compare groups/populations

Likert Scales

Needs to have order and equal value

3 Steps

1. Present

2. Describe, In describing, explain the most indicative result, The mean is usually the most indicative

3. Analyse, Make Meaning of the data

Averages

Mean, Parametric, Uses the bell curve

Median, Middle score in the rankings

Mode, Most common score

Excel Proficiency

Correlation

Mean, Median, mode