Additional results of PCA

PCA models in R produce additional diagnostic and output components:

center: the column means used to center to the data, or FALSE if the data weren't centered
scale: the column standard deviations used to scale the data, or FALSE if the data weren't scaled
rotation: the directions of the principal component vectors in terms of the original features/variables. This information allows you to define new data in terms of the original principal components
x: the value of each observation in the original dataset projected to the principal components

You can access these the same as other model components. For example, use pr.out$rotation to access the rotation component.

Which of the following statements is not correct regarding the pr.out model fit on the pokemon data?

The x component is a table with the same dimensions as the original data.
The data were centered prior to performing PCA.
The data were scaled prior to performing PCA.
The directions of the principal component vectors are presented in a table with the same dimensions as the original data.