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 – 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

Table Showing of Principal Component Analysis


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