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Curricular information is subject to change
Upon completion of this module, students should be able to:
Understand and choose basic statistical analyses, including descriptive statistics, chi square and t tests, ANOVA models, correlation and simple linear regression, and selected non-parametric tests.
How to report methods and findings in accordance with best practice.
How to correctly interpret and critique the results of numerical analyses of biological, medical or related data.
- Data and descriptive statistics
- The Normal and other distributions
- Comparing means and proportions between groups: t tests and chi-square tests
- Comparing many means: between-subjects ANOVA, within-subjects ANOVA, mixed ANOVA
- Correlation
- Linear regression
- Non-parametric tests
- Error, bias and reliability
- Trends in the transparent use of statistics in research
Student Effort Type | Hours |
---|---|
Tutorial | 12 |
Computer Aided Lab | 12 |
Specified Learning Activities | 30 |
Autonomous Student Learning | 54 |
Online Learning | 12 |
Total | 120 |
Not applicable to this module.
Resit In | Terminal Exam |
---|---|
Spring | No |
• Feedback individually to students, on an activity or draft prior to summative assessment
• Feedback individually to students, post-assessment
• Group/class feedback, post-assessment
Feedback on weekly formative (not graded) exercises will be given on request or automatically by the VLE, in advance of the Computer Lab assessment. Feedback on the computer lab assessment will be given individually to students through the VLE. General feedback will be given to the full class through the VLE.
Name | Role |
---|---|
Ms Carolyn Ingram | Lecturer / Co-Lecturer |