The dataset on American college and university rankings contains information on 1302 American colleges and universities offering an undergraduate program. For each university, there are 17 measurements (variables) that include continuous (e.g. tuition and graduation rate) and categorical measurements (e.g. location by state and whether it is a private or a public school). The data are in the file University.xls

1. a)  Remove all categorical variables. Then handle missing values by removing all records with missing numerical measurements from the dataset. (Use XLMiner Missing Value Handling tool).

2. b)  Conduct a principal components analysis on the cleaned data and comment on the results. Should data be normalized?

3. c)  As you remember, new variables (principals) are the linear combinations of the original variables. If we follow up the coefficient values, discuss which variables characterize the principals you consider to work with.

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