Question 1: PCA analysis [85 marks] Perform the following in SAS (ensure to include your code and outputs and interpretations): a) b) o d) ) g) by i) D k) Perform a principal component analysis using SAS on the correlation matrix for the 9 ADME variables. Show your full SAS code and output. (10 marks) Ensure you obtain the following 5 types of plots related to PROC PCA. (All plots should be placed in clearly labelled Appendices). (10 marks) * Scree plot + Profile plot Component Pattern plots * Score plots * Loading Plots Report the eigenvalues and the eigenvectors. (5 marks) What percentage of the total sample variation and cumulative variation is accounted for by each of the PCs? (5 marks) Write out the formulation for the PCs. (10 marks) Interpret the PCs via eigenvalues, your component pattern profiles AND your loading plots from SAS. (10 marks) Label your score plot for PC2 versus PC1 by violator and non-violator status and summarise any trends and findings. (5 marks) Label your score plot for PC2 versus PC1 by oral status and summarise any trends and findings. (5 marks) Label your score plot for PC3 versus PC2 by violator and non-violator status and summarise any trends and findings. (5 marks) Label your score plot for PC3 versus PC2 by oral status and interpret any trends and findings. (5 marks) Using BOTH a formal test of hypothesis and relevant plots can the data be effectively summarized in fewer than 9 dimensions. k