An Adventure in Statistics (976C8)
An Adventure in Statistics
Module 976C8
Module details for 2025/26.
15 credits
FHEQ Level 7 (Masters)
Module Outline
An adventure in statistics consists of a series of lectures and practical classes, mainly aimed at introducing or re-introducing postgraduate students to statistical models. The lectures are aimed at delivering background theory and the practical classes are designed around interactive tutorials that put the theory from the lecture into practice using the open source (and free) statistics software R (implemented in RStudio). Through these tutorials students should develop a good working knowledge of RStudio (and R).
Topics may include:
The linear model
Key concepts (parameters, estimation, standard error, confidence intervals)
Hypothesis testing, effect sizes and Bayes factors
Bias and assumptions of the linear model
Categorical predictors in the linear model (ANOVA)
Factorial designs and covariates
Repeated measures deisgns
Multilevel models (HLM)
Growth models
Categorical outcomes (logistic models)
Implimentation of the above in R and RStudio
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 the software R (and the RStudio IDE)
Self-reflect upon ones understanding of the theory and application of a range of statistical models
| Type | Timing | Weighting |
|---|---|---|
| Coursework | 55.00% | |
| Coursework components. Weighted as shown below. | ||
| Take Away paper | T1 Week 6 (48 hours) | 45.00% |
| Take Away paper | T1 Week 9 (48 hours) | 55.00% |
| Report | Semester 1 Assessment Week 1 Wed 16:00 | 45.00% |
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 | Practical | 2 hours | 22111111111 |
| Autumn Semester | Lecture | 1 hour | 22111121111 |
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
Convenor, Assess convenor
/profiles/9846
Dr Dominique Makowski
Convenor
/profiles/592424
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