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Qualitative Data Analysis Using Open Coding Gender difference, anxiety and fear of crime 1995

Assignment Requirements
 
 
use the instructions in task  description and instructions to do the work files. You need to use the open code. The data used are in files int1 and int2. You should also consider the lecture notes provided in the power point file.
 
Qualitative assignment.
This assignment is a 3500 word qualitative data analysis.  You will examine a data set called “ Gender difference, anxiety and fear of crime 1995” which will be posted on the Moodle.   You are required to analyse Two interview transcripts using your own preferred method, and write a report. This assignment contributes 35% to total mark for this unit.
In your report, you need to pay attention to the following:

Description of analytical framework (thematic approach, grounded theory, narrative analysis etc). Your chosen analytical framework must be clearly outlined.
You should provide a detailed account of the processes and procedures for analysis of data and examples  of analysis.
You need to show evidence and description of advanced analysis beyond open coding.

  When quoting from the transcripts to highlight your findings, you need to provide explanation as to why particular quotes were selected (e.g. are they representative, illustrative, etc.).  Please remember to reference the source.

Provide enough information of how themes, categories or concepts were derived from the data. If using Nvivo, you can illustrate how you progressed from free nodes to tree nodes.

Be reflexive about your own role as the analyst/researcher, and your methodological approach, and how this relates to your findings.
The results should appear consistent and appropriate, relating back to the research questions.

Allocation of Marks:

Introduction   and literature review                        20%
Methodology and research design                          15%
Data analysis                                                           30%
Findings and discussion                                          20%
Conclusions                                                             10%

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