Statistics with R and RStudio

About

We are exposed to statistical data daily in the form of opinion polls, economic forecasts, reports on the effect of diet and lifestyle on life expectancy and disease risk, debates over the evidence for climate change, among others.

This module introduces statistics and the free software R/RStudio to you with no previous knowledge of mathematics beyond high school level.

This module also assesses the uses, misuses and limitations of statistical methods.

Topics range from basic descriptive statistics to more advanced topics including multivariate analysis, logistic regression, and model optimisation.

As additional skills, you are introduced to professional-standard plotting resources, basic programming functions in R, and the user-friendly RStudio interface.

Week one
Introduction to statistics and the RStudio interface
Descriptive statistics, probability distributions and confidence intervals
Hypothesis testing: t-tests and their non-parametric alternatives

Week two
ANOVA
Chi-square and other proportion tests
Power analysis and sample size calculation
Linear and multiple regression

Week three
Multivariate analysis: PCA
Logistic regression, interactions and model optimisation

Course leader

Dr Lucio Vinicius

Course aim

This module aims to:

- Provide a general introduction to statistics for students with no mathematical background beyond high‑school level.
- Deliver a package of statistical techniques ranging from basic hypothesis testing to more sophisticated procedures.
- Enable you to select and run appropriate statistical tests independently, create professional‑level graphs and presentations, and critically evaluate statistical information in technical reports and the general press.
- Provide sufficient statistical knowledge to qualify you for further study or a professional position requiring quantitative analytical skills.

Fee info