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38 lines
1.9 KiB
Plaintext
38 lines
1.9 KiB
Plaintext
# Prep work (JK):
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- JK: aggregation of free-text answers: Q17, Q18 so that they can be used for subsetting
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# Basic summary visualisations (RH):
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- Q2 (respondent age)
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- Q3 (year of study)
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- Q16 (gender identity)
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- Q17 (ethnic self-id)
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- Q18 (religion)
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# Visualisations of LIKERT responses (RH):
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- For questions Q6 (subject interest) / Q5 (subject knowledge) / Q7 employability prospects:
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- visualisation as summaries for all subjects LIKERT data as stacked bar chart (colours for bar segments from cool to warm)
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- separate visualisation of summary data as pie chart only for 4 key subjects: Philosophy, Ethics, Theology, Religious Studies, but with data represented as aggregated "Positive" / "Negative" responses
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- subsetted visualisations of responses with separate subsetting by response to Q8-9, Q18, Q17, Q16
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- For question Q8 + Q9 (for religious people)
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- visualisation summary of responses
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- show subsetted visualisations of responses by response to, Q18, Q17, Q16, Q13, Q14
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- For responses to Q10-12 (what subjects are involved in...):
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- represent answer counts as descending bar chart for each Q
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- subset answers by Q6 (positive / negative) and Q5 (positive / negative)
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# Correlation testing:
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- For Q6 (subject interest) / Q5 (subject knowledge) / Q7 employability prospects, test for nature / strength of correlation with responses to:
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- Q8-9 responses
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- Q18 responses
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- Q17
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- Q18
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For later:
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- JK: calcuate baseline comparator using UCAS application data for Q5/6, stack with UOB application data for key subjects + 2-3 other samples
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Bonus, if time permitting:
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- show numeric count with percentage calc of total for "prefer not to say" and "Neither/Nor" responses on bar chart for Q5/Q6/Q7
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- test for correlations between responses to Q10-12 and Q5-7
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- create sankey visualisation of answers on Q6/5/7 with Religion / Theology
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- create concept map visualisation of answers on Q5-7
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- create sunburst style visualisation to represent subsetting on Q5-7 |