Need help with this predictive modeling homework. We use tool called jmp pro.

Use the "Telephone Calls" data set. a. Find the number of outliers with "Tail Quantile" = 0.1 and Q=3 (Note that Q is a multiplier used to determine outliers for the chosen variable). How many outliers are there in the data set? Copy the table that shows the number of outliers for each variable. b. Find the number of outliers with "Tail Quantile" = 0.3 and Q=3. How many outliers are there in the data set? Copy the table that shows the number of outliers for each variable. c. After detecting the outliers in part b, remove the outliers from the data set. How many observations do you have after removing the outliers? d. After removing the outliers in part c, detect the number of missing values. Copy the window that demonstrates the number of missing values in each variable. Part of the table is shown below. Missing Columns Show only columns with missing Column Missin e. Impute the missing values using Multivariate Normal Imputation. Copy the "Imputation Report" that occurred at the same window with "Missing Columns" as shown in the sample picture. 4 Imputation Report Undo missing values were replaced by least squares imputation. A shrinkage estimate was used, with off diagonals scaled by a factor rows and @columns were affected. There were missing value patterns across columns, Imputed values colored light blue Missing Columns Number Show only columns with missing Column Missing f. Apply hierarchical clustering to the clean data set. Copy the dendrogram and report the number of recommended clusters in the final data set. g. Use k-means clustering to the clean data set with k=15 through 25. What is the optimal number of clusters using the optimal CCC value? Focu