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Exercise

Variance explained

The second common plot type for understanding PCA models is a scree plot. A scree plot shows the variance explained as the number of principal components increases. Sometimes the cumulative variance explained is plotted as well.

In this and the next exercise, you will prepare data from the pr.out model you created at the beginning of the chapter for use in a scree plot. Preparing the data for plotting is required because there is not a built-in function in R to create this type of plot.

Instructions
100 XP

pr.out and the pokemon data are still available in your workspace.

  • Assign to the variable pr.var the square of the standard deviations of the principal components (i.e., the variance). The standard deviation of the principal components is available in the sdev component of the PCA model object.
  • Assign to the variable pve the proportion of the variance explained, calculated by dividing pr.var by the total variance explained by all principal components.
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