.Download churn dataset from blackboard and perform the followings . Explore whether there are missing values for any of the variables - If they are, correct them by replacing with new data - Use a graph to visually determine whether there are any outliers among the number of calls to customer servioe . - Transform the day minutes attribute using Zscore standardization . University Rankings. The dataset on American college and university rankings [available from blackborad ]contains information on 13432 American colleges and universities offering an undergraduate program For each university there are 1? measurements that include continuous measurements [such as tuition and graduation rats J and categorical measurements {such as location by state and whether it is a private or a public school I. a} Remove all categorical variables . Then remove all reoords with missing numerical measurements from the dataset {by creating a new object}. You only need to write down the R code and the first 3 rows of the new dataset . b} Conduct a principal components analysis on the cleaned data and comment on the results. Write done the first couple of new variables which are the linear combination of original variables c} Should the data be normalized '9 Discuss what characterizes the components you consider key. Perform PCA on normalized data. Write down the new components and compare this result with b]