1600 words MINIMUM (not including cover/reference pages or questions)

Requirement is at least five scholarly articles, ONE maybe the course textbook BELOW

Textbook(s)

Mirabella, J. (2011). Introduction to Statistics.

Nashville, TN: Savant Learning Systems.

UNIT 7 Complete

Use the Student_Data which consists of 200 MBA students at Whatsamattu U. It includes variables regarding their age, gender, major, GPA, Bachelors GPA, course load, English speaking status, family, and weekly hours spent studying.

1. Does undergraduate success predict graduate success? While most people complete their bachelor’s degree during the daytime while taking multiple classes and not working full-time, those getting an MBA are typically taking one or two courses at a time, in the evening or on weekends, and while working and even supporting a family. Yet one would expect those who perform better in their bachelor’s degree will perform better in their master’s. Using a significance level of .05, test whether there is a correlation between the BS GPA and the MBA GPA. Also, answer the following:

a) What is the correlation coefficient & how strong is it?

b) What is the best fit regression equation that can predict the MBA GPA from the BS GPA?

c) What percent of the variability in the MBA GPA can be explained by the regression model?

d) What would you expect a student’s MBA GPA to be if he/she had a 3.50 BS GPA?

2. To get an even better model for predicting MBA performance, let’s look at many variables. Create a multiple regression model predicting the MBA GPA using the BS GPA, the Hours studied per week, the Gender of the student, whether the student works full-time, and the student’s age. Use a .05 significance level. After you create your model, predict the MBA GPA 40-year old student that studies 6 hours per week, works full-time, and had a 3.00 BS GPA.