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In this course, you will :
- explains how to use Microsoft Excel to perform cluster analysis and principal component analysis, which tends to show more clearly what's going on in the analysis
- demonstrates how to perform the same analysis using R, an open-source statistical computing software that is faster and has more analysis options than Excel.
- demonstrates how to combine the results of cluster analysis and factor analysis to help you break down a few underlying factors based on individuals' membership in only a few clusters.
Syllabus :
1. Problems Raised by Massive Amounts of Data
- Observation overkill
- Rationale for clustering
- Rationale for PCA
2. An Overview of Principal Components Analysis
- Using Excel to extract principal components
- Rotating factors
- Using R to extract principal components
3. An Overview of Cluster Analysis
- ANOVA and MANOVA reviewed
- Causation and probability
- Multivariate nature of clustering
- Using R for cluster analysis
- Using Excel for cluster analysis
- Setting up confusion tables in Excel
4. Putting It Together: Using Cluster Anaysis and Factor Analysis in Concert
- Clusters and factors
- Pivot table analysis
