Imagine you are interested in knowing how variables like GRE (Graduate Record Exam scores), GPA (Grade Point Average) etc affect admission into graduate school. The response variable,"admit"(admit/don't admit), is a binary variable(admit = 1 / don't admit = 0).

The logistic regression model using the datasetbinary.csv(https://www.dropbox.com/s/txg9spn5rabibdf/binary.csv?dl=0)

. Use the information from the model to answer the following five questions. Select the closest answer.

note:You might want to use this code to read the file:

read.csv("binary.csv",fileEncoding="UTF-8-BOM")

A student has the GPA of 3.5 and GRE score of 330. What is the predicted probability of this student getting admitted into graduate school?

A: exp(-4.949 + 0.003*3.5 + 0.755*330)/[1 + exp(-4.949 + 0.003*3.5 + 0.755*330)]

B: exp(-4.949 + 0.003*330 + 0.755*3.5)/[1 + exp(-4.949 + 0.003*330 + 0.755*3.5)]

C: [1 - exp(-4.949 + 0.003*330 + 0.755*3.5)]/[1 + exp(-4.949 + 0.003*330 + 0.755*3.5)]

D: [1 - exp(-4.949 + 0.003*330 + 0.755*3.5)]/exp(-4.949 + 0.003*330 + 0.755*3.5)