# 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 β each variableΥs 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 |

1.00Υs 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 |

β Manishika