# Factor Analysis and PCA YouTube Lecture Handouts: Factor Analysis and PCA Analysis

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## Factor Analysis

• Reduce large number of variables into fewer number of factors
• Co-variation is due to latent variable that exert casual influence on observed variables
• Communalities – each variable՚s variance that can be explained by factors

## Principal Component Analysis

• Variable reduction process – smaller number of components that account for most variance in set of observed variables
• Explain maximum variance with fewest number of principal components
 PCA Factor Analysis Observed variance is analyzed Shared variance is analyzed 1.00՚s are put in diagonal – all variance in variables Communalities in diagonal – only variance shared with other variables are included – exclude error variance and variance unique to each variable Analyze variance Analyze covariance

Manishika