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 
 

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 

Topics

  • Preparing a multivariate dataset for analysis. 
  • Principal Components Analysis. 
  • Factor Analysis. 
  • Cluster Analysis. 
  • Discriminant Analysis 

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
























 

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. 

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