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School of Psychology

Discovering Statistics (C8552)

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

TypeTimingWeighting
Coursework60.00%
Coursework components. Weighted as shown below.
ReportT1 Week 11 50.00%
PortfolioT1 Week 11 (2 hours 30 minutes)8.30%
Computer Based ExamT1 Week 11 41.70%
Unseen ExaminationSemester 1 Assessment40.00%
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.

TermMethodDurationWeek pattern
Autumn SemesterOnline Laboratory Practical2 hours11111111111
Autumn SemesterLecture1 hour22111111110
Autumn SemesterPractical2 hours11111111111
Autumn SemesterLecture1 hour11111111111

How to read the week pattern

The numbers indicate the weeks of the term and how many events take place each week.

Prof Andy Field

Assess convenor, Convenor
/profiles/9846

Dr Reny Baykova

Convenor, Assess convenor
/profiles/386580

Dr Danielle Evans

Assess convenor, Convenor
/profiles/414983

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