Foundations of OR: Statistical Methods in OR: Multivariate Models
A practical course using multivariate statistical techniques to gain greater insights from your analysis.
Description
- Advance your analytical skills using a range of multivariate statistical techniques.
- Gain more detailed insight from your analysis by exploring multiple variables simultaneously to find patterns and correlations.
- Increase your confidence using multivariate techniques to analyse complex datasets.
Learning objectives
- Prepare a multivariate dataset for analysis.
- Apply Principal Components Analysis and interpret the results.
- Apply Factor Analysis and interpret the results.
- Apply Cluster Analysis and interpret the results.
- Apply Discriminant Analysis and interpret the results.
- Learn when to use these different statistical techniques
Topics
- Preparing a multivariate dataset for analysis.
- Principal Components Analysis.
- Factor Analysis.
- Cluster Analysis.
- Discriminant Analysis
Audience
Anyone interested in getting an overview of multivariate statistical techniques.
Participants should be familiar with basic statistical analysis as covered in the related course: Foundations of O.R: Statistical Methods in OR: Descriptive Statistics, Sampling and Regression.
Course format
- Powerpoint presentation to introduce the techniques
- Practical sessions using SPSS software
- Case studies based on ‘real world’ problems
- Group discussion/work to interpret the results
- Bring questions from your own work to embed your learning
- Supporting resource pack available to use following the course
Related courses
- Foundations of OR: Follow on to Forecasting: ARIMA modelling for forecasting
- Foundations of OR: Optimisation and (Meta-) Heuristics
- Foundations of OR: Data Envelopment Analysis