Loadings and scores for the PCs
The primary goal of PCA is dimension reduction, which is often necessary to view high dimensional data. Plotting the PC scores in two dimensions is one way to visualize high dimensional data.
This exercise is part of the course
Multivariate Probability Distributions in R
Hands-on interactive exercise
Have a go at this exercise by completing this sample code.
# Create data frame of scores
scores.state <- data.frame(___)
# Plot of scores labeled by state name
ggplot(data = scores.state, aes(x = ___, y = ___, label = ___) +
geom_text( alpha = 0.8, size = 3) +
ggtitle("PCA of states data")