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

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Factor Analysis and Principal Component Analysis

## 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 β each variableβs variance that can be explained by factors

## Principal Component Analysis

• Variable reduction process β 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 1.00βs are put in diagonal β all variance in variables Communalities in diagonal β only variance shared with other variables are included β exclude error variance and variance unique to each variable Analyze variance Analyze covariance