Introductory description

This module will introduce students to the R data analysis package and to a range of statistical analysis tools. Students will get hands on experience with analysing real datasets in R, with extensive support and guidance from teaching staff. They will learn how to identify the correct statistical tools to use to answer different business related questions, and how to interpret the results.

Module web page

Module aims

Outline syllabus

This is an indicative module outline only to give an indication of the sort of topics that may be covered. Actual sessions held may differ.

Introduction to R
Visualising Data in R
The General Linear Model: t-tests
Estimation: Confidence Intervals
Correlation and Simple Linear Regression
The General Linear Model: Regression
The General Linear Model: ANOVA
The General Linear Model: Repeated Measures
The Generalised Linear Model: Logistic Regression

Learning outcomes

By the end of the module, students should be able to:

• Demonstrate comprehensive understanding of null hypothesis significance testing and contrast this with the estimation approach
• Plan an analysis of, and think critically about, data

Indicative reading list

Reading lists can be found in Talis

Subject specific skills

Conduct reproducible statistical analysis using the general and generalised linear model
Construct 4* publication quality visualisations of data

Transferable skills

Written communication.
Problem solving.