Module information

General structure of the module

This module is a little different to most of your other mathematics modules, as it runs across both semesters (in the module jargon, we sometimes call this a long, thin module. There will be 22 lectures (one per week) in which we’ll largely cover the required theory. These will be complemented by fortnightly practicals each of length two hours in which we’ll build up skills in the statistical package RStudio and meet practice problems analogous to those you receive on problem sheets in other modules. It will often be the case that you will not complete all the work set in a practical within the two hour session itself, so do expect to have to dedicate some time outside of practicals.

The pen-and-paper parts of the module are primarily assessed through a two-hour exam in the May exam period, which is worth 60% of the module mark. The other 40% of the mark assesses your practical statistics skills through a report on a dataset using RStudio (semester one, worth 20%) and an assessed practical which is essentially a short open-book computer exam (semester two, worth 20%).

Important dates

The report on a dataset assignment will be made available in Practical 4 on Friday 15th November 2024. You’ll have just under two weeks to complete the task set there, with the deadline being 5pm on Thursday 28th November 2024.

The assessed practical in semester two will take place in the practical in the week commencing 24th March 2025 (at time of writing, Thursday 27th March 2025, though it’s possible the timetable will change before then).

Marking criteria for assignment one

P3.Q1 will be marked according to the mathematical correctness of answers. [20 marks]

For the report on the given dataset [80 marks], marks will be awarded for the following categories:

  • Introduction and Conclusion: 10

  • Tables: 10 (3 - Plot choice, 3 - Plot editing, 4 - Interpretation)

  • Barplots: 10 (3 - Plot choice, 3 - Plot editing, 4 - Interpretation)

  • Boxplots: 10 (3 - Plot choice, 3 - Plot editing, 4 - Interpretation)

  • Scatterplots: 10 (3 - Plot choice, 3 - Plot editing, 4 - Interpretation)

  • Further Investigations 20

  • Presentation: 10

Reading list

A full reading list is available here on Talis Aspire. The book I’d recommend the most for the lecture content of this module is Mathematical Statsitics with Applications by Wackerly, Mendenhall, and Sheaffer. There are many good books and websites that can help learning R/RStudio including those in the reading list that’s linked above.

Learning outcomes

On successful completion of this module students should be able to:

  1. Summarise effectively a set of data;

  2. Identify the statistical techniques appropriate to analysing a given situation;

  3. Carry out standard statistical procedures for one and two samples;

  4. State and check the assumptons required by their analyses;

  5. Draw conclusions from an analysis of data and write reports concerning these conclusions;

  6. Interpret one-way and two-way ANOVA tables, and interaction diagrams;

  7. Use the statistical package ‘R’ to practically manipulate and analyse datasets.

Overview of content

The following is an outline of the topics to be covered in this module:

  1. DESCRIPTIVE STATISTICS: Interpretation of data presented in numerical and graphical forms. Report writing.

  2. REGRESSION: Fitting straight lines, correlation coefficient, multiple regression.

  3. DISTRIBUTIONS: Bionomial, Poisson, Normal etc. Distribution of the sample mean. Graphical assessment of goodness of fit; Q-Q plots.

  4. BASIC IDEAS: Estimates and standard errors of means, proportions, sums and differences.

  5. CONFIDENCE STATEMENTS: Construction and interpretation of confidence intervals for means, rates and proportions. Bootstrap confidence intervals. Confidence limits for the difference between parameters.

  6. HYPOTHESIS TESTING: Hypothesis tests; interpretation of p-values. Paired an unpaired two sample t-tests. Bootstrap p-values.

  7. GOODNESS-OF-FIT: Chi-squared test.

  8. DESIGNED EXPERIMENTS: One-way ANOVA. Two-way ANOVA. Interactions.

Further information

Definitive module information is available on the Aberystwyth University module pages.