Discovering Statistics (C8552)
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Discovering Statistics
Module C8552
Module details for 2025/26.
15 credits
FHEQ Level 5
Full Module Description
This module deepens students’ theoretical understanding and practical skill in implementing, interpreting, and reporting the results of statistical analyses, based around the overarching theme of the linear model. There are weekly lectures that cover statistical principles in depth, each accompanied by an online tutorial to help students develop and test their understanding. Practical classes compliment the lectures by providing guidance on applying the general linear model, advice on designing and executing projects, and conducting experimental research, and encourage consistent development of statistical skills and critical thinking through weekly quizzes. The statistical analysis parts of the module build upon existing knowledge of statistical theory to enable students to analyse more complex data structures through understanding the general linear model (regression, ANOVA etc.). There are two assessed piece of coursework using some of these techniques, which will enable students to progress their skills in critical thinking, analysis, and use of statistical software, and which will therefore equip students for their empirical research projects.
This module builds on knowledge gained in the core psychology modules C8511: Psychology as a science and C8891: Analysing data. Students who are not enrolled on the BSc Psychology course at Sussex are expected to be familiar with the material covered in these modules.
Module Outline
This module deepens students’ theoretical understanding and practical skill in implementing, interpreting, and reporting the results of statistical analyses, based around the overarching theme of the linear model. There are weekly lectures that cover statistical principles in depth, each accompanied by an online tutorial to help students develop and test their understanding. Practical classes compliment the lectures by providing guidance on applying the general linear model, advice on designing and executing projects, and conducting experimental research, and encourage consistent development of statistical skills and critical thinking through weekly quizzes. The statistical analysis parts of the module build upon existing knowledge of statistical theory to enable students to analyse more complex data structures through understanding the general linear model (regression, ANOVA etc.). There are two assessed piece of coursework using some of these techniques, which will enable students to progress their skills in critical thinking, analysis, and use of statistical software, and which will therefore equip students for their empirical research projects.
This module builds on knowledge gained in the core psychology modules C8511: Psychology as a science and C8891: Analysing data. Students who are not enrolled on the BSc Psychology course at Sussex are expected to be familiar with the material covered in these modules.
Module learning outcomes
Demonstrate a systematic understanding of the theory and application of a range of statistical models
Initiate, execute, and interpret a range of statistical models fitted using R
Initiate, implement, critique, and communicate research methodologies applied to psychological questions
| Type | Timing | Weighting |
|---|---|---|
| Coursework | 60.00% | |
| Coursework components. Weighted as shown below. | ||
| Report | T1 Week 11 | 50.00% |
| Portfolio | T1 Week 11 (2 hours 30 minutes) | 8.30% |
| Computer Based Exam | T1 Week 11 | 41.70% |
| Unseen Examination | Semester 1 Assessment | 40.00% |
Timing
Submission deadlines may vary for different types of assignment/groups of students.
Weighting
Coursework components (if listed) total 100% of the overall coursework weighting value.
| Term | Method | Duration | Week pattern |
|---|---|---|---|
| Autumn Semester | Online Laboratory Practical | 2 hours | 11111111111 |
| Autumn Semester | Lecture | 1 hour | 22111111110 |
| Autumn Semester | Practical | 2 hours | 11111111111 |
| Autumn Semester | Lecture | 1 hour | 11111111111 |
How to read the week pattern
The numbers indicate the weeks of the term and how many events take place each week.
Dr Reny Baykova
Convenor, Assess convenor
/profiles/386580
Dr Danielle Evans
Convenor, Assess convenor
/profiles/414983
Prof Andy Field
Assess convenor, Convenor
/profiles/9846
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