Perform principal component analysis on the accompanying data set.
Use the data with the Covariance method and choose Smallest number components explaining at least: of variance.
a How many principal components were created?
a What percent of total variance is accounted for by the calculated principal components?
Note: Round intermediate calculations to at least decimal places and your final answer to decimal places.
aWhat are the weights for computing the first principal component scores?
Note: Round intermediate calculations to at least decimal places and your final answers to decimal places. Negative values should be indicated by a minus sign.
Use the data with the correlation matrix to perform PCA. Keep all the other options the same as in part a
b How many principal components were created?
b What percent of total variance is accounted for by the calculated principal components?
Note: Round intermediate calculations to at least decimal places and your final answer to decimal places.
bWhat are the weights for computing the first principal component scores?
Note: Round intermediate calculations to at least decimal places and your final answers to decimal places. Negative values should be indicated by a minus sign.