Principal Components Analysis resources
Principal Components Analysis (Worksheet)
Principal Components Analysis (PCA) is a multivariate technique aimed at reducing the number of variables in your data set so that your new variables (components) are uncorrelated. This teach yourself worksheet gives a very brief introduction to PCA and how to perform this using SPSS. This includes some useful references at the end. Note: The "Analyze" --> "Data Reduction" step in SPSS (see page 2) in SPSS has now been changed to "Analyze" --> "Dimension Reduction"
The Statistics Tutor's Quick Guide to Commonly Used Statistical Tests
A handy quick guide to statistical tests and techniques for those providing statistics support. This covers when to use each technique along with the interpretation of results, checking assumptions and what to do if the assumptions are not met. This was developed by the MASH Centre at the University of Sheffield and contributed to the statstutor Community Project by Ellen Marshall (University of Sheffield) and Alun Owen (University of Worcester) and reviewed by Jean Russell and Nick Fieller, (University of Sheffield).