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

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Watch Video Lecture on YouTube: Factor Analysis and Principal Component Analysis

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 – 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