Multivariate analysis
Overview
This course provides practical materials and background information on the analysis of multivariate data.
Learning Objectives
After this course participants should be able to:
- perform Principal Component Analysis (PCA)
- perform K-means clustering
- perform basic hierarchical clustering
Target Audience
Participants are generally those who need to analyse data that contain many different variables. They can be graduate or postgraduate students, or researchers who find themselves having to do this.
Prerequisites
Participants should have some knowledge regarding statistics. Attending the Core statistics course is recommended.
More importantly, participants should have a working knowledge of either R or Python, since the topics that are covered require data wrangling and visualisation.
Exercises
Exercises in these materials are labelled according to their level of difficulty:
| Level | Description |
|---|---|
| Exercises in level 1 are simpler and designed to get you familiar with the concepts and syntax covered in the course. | |
| Exercises in level 2 combine different concepts together and apply it to a given task. | |
| Exercises in level 3 require going beyond the concepts and syntax introduced to solve new problems. |