Question: After applying Principal Component Analysis ( PCA ) on five variables from the Breakfast Cereals dataset ( calories , protein, fat, sodium, and fiber )

After applying Principal Component Analysis (PCA) on five variables from the Breakfast Cereals dataset (calories, protein, fat, sodium, and fiber), the importance of components are summarized below: PC1PC2PC3PC4PC5Standard deviation84.047418.555272.371060.917530.80417Proportion of Variance0.95260.046430.000760.000110.00009Cumulative Proportion0.95260.999040.99980.999911 The rotation matrix is: PC1PC2PC3PC4PC5calories0.0730.996-0.0320.0270.021protein-0.0010.002-0.289-0.8210.493fat0.0000.028-0.091-0.489-0.867sodium0.997-0.0730.000-0.002-0.001fiber-0.002-0.037-0.9520.295-0.067 The mean of the five variables are listed below: Meancalories106.883protein2.545fat1.013sodium159.675fiber2.152 Data of three Breakfast Cereals products are given below:Cereal ProductcaloriesproteinfatsodiumfiberCrispix110202201Cheerios110622902Total_Raisin_Bran140311904 Round your answers to 3 digits after the decimal point.The value of PC1 of Crispix is .The value of PC2 of Crispix is .The value of PC1 of Cheerios is .The value of PC2 of Cheerios is .The value of PC1 of Total_Raisin_Bran is .The value of PC2 of Total_Raisin_Bran is .

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