What is the exact difference between principal component analysis (PCA)and principal component regression (PCR)? With what kind of data sets can one use these methods?
Principal component analysis is a method of data reduction - representing a large number of variable by a (much) smaller number, each of which is a linear combination of the original variables.
One output of PCA is principal component scores. Principal component regression uses those scores as independent variables in a regression.