The underlying, mathematical objective in principal components analysis is to obtain:

a. Correlated linear combinations of the original variables that account for as much of the total variance in the original variables as possible

b. Uncorrelated linear combinations of the original variables that account for some of the total variance in the original variables

c. Uncorrelated linear combinations of the original variables that account for as much of the total variance in the original variables as possible

d. Uncorrelated combinations of the original variables that account for as much of the total variance in the original variables as possible