For the data set with the attributes given below, describe how you would convert it into a binary transaction data set appropriate for association analysis. Specifically, indicate for each attribute in the original data set

how many binary attributes it would correspond to in the transaction data set, how the values of the original attribute would be mapped to values of the binary attributes, and if there is any hierarchical structure in the data values of an attribute that could be useful for grouping the data into fewer binary attributes.

The following is a list of attributes for the data set along with their possible values. Assume that all attributes are collected on a per$-$student basis:

Year: Freshman, Sophomore, Junior, Senior, Graduate:Masters, Graduate:PhD$,$ Professional

Zip code: zip code for the home address of a U$.$S$.$ student, zip code for the local address of a non$-$U$.$S$.$ student

College: Agriculture, Architecture, Continuing Education, Education, Liberal Arts, Engineering, Natural Sciences, Business, Law, Medical, Dentistry, Pharmacy, Nursing, Veterinary Medicine

On Campus: $1$ if the student lives on campus, $0$ otherwise

Each of the following is a separate attribute that has a value of $1$ if the person speaks the language and a value of $0,$ otherwise.

Arabic

Bengali

Chinese Mandarin

English

Portuguese

Russian

Spanish