Can I have a solution for this case:

KUSB MBA Admission Guidelines

The MBA program at Kurtosis University (KUSB) has undergone several dramatic changes over the past five years.During that time, the goal of the business school was to recruit as many students as possible into the MBA program to build up their student base and credit hour production. A massive media campaign was launched five years ago to attract more applicants to the program.

• Special brochures containing information about the program were printed and mailed to prospective students as well as to other colleges and universities that were likely to have undergraduate students who might be interested in coming to KUSB.
• Mailings were also sent to students who indicated an interest in KUSB on their GMAT exam. (The GMAT exam is a national standardized test used by most business schools in making admissions decisions for applicants to their graduate programs.)
• Representatives from KUSB began attending regional MBA fairs and conventions where MBA programs can meet with prospective MBA students and share Information.

In the beginning, the number of students applying to the KUSB MBA program was small, but eventually, the advertising campaign began to work and the number of qualified applicants each year increased to the target value of 300 initially set by the dean of the business school and the director of the MBA program.The table below shows the admissions and enrollment figures for the five years of the MBA student base-building plan at KUSB. The yield (i.e., the number of admitted applicants who enroll and attend KUSB) is typically around 80%.Admitted students who do not enroll either attend other MBA programs or accept job offers.

Year	Admissions	Enrollment	Enrollment/Admission Ratio
1	116	94	81%
2	138	109	79%
3	164	135	82%
4	186	158	85%
5	205	167	81%

Phase 2

Albert Razzick, the director of the program, is currently putting the second phase of the plan into action.He knows that for the MBA program at KUSB to attain national recognition, they must become more selectivein the admissions process.The number of applicants is now large enough to do this without falling below a critical mass of 60 enrolled students each year.

The major issue facing Albert and the MBA program is how to go about selecting students for the program.Albert recently met with Dr. Kathleen Thompson, who is a finance professor to discuss how they can improve their admissions process. Albert shared his intentions of making the program better. He wants to make sure he can get the best 100 students to the program next year.

Current Standards

Their current standards of minimum GMAT and minimum UG GPA had to be abandoned.

He suggested a formula approach where a score is calculated by multiplying the UGGPA by a constant and adding the GMAT score i.e.: SCORE = GMAT + 200 * UGGPA.

Kathleen agrees with a formula approach but suggests that it should be extended to include other relevant variables such as their undergraduate school and major, whether they are local or international studentsand even other relevant variables if data is available for analysis.

After a long conversation, Kathleen and Albert agreed that KUSB should develop their own formula with as many variables as they can get to improve their methodology's prediction power. Further discussion led them to decide to use the first-year GPA in their MBA program to judge whether the student is successful or not. They decided to consider the student "successful" if she/he have an MBA GPA greater than 3.2 at the end of the first year. They are also aware of the fact that not all students will achieve that GPA and that is fine with them.

Albert promised Kathleen that he would gather the data for the lasttwo yearsof students who are already in the program to build the admissions model.

Assignment

Albert Razzick's assistant gathered the data for the pasttwo yearsof experience with the KUSB MBA program and stored the information in the attached file.Using this data set and other information given in the case, help Albert Razzick develop admissions guidelines for the KUSB MBA program. You should decide on the best regression model to predict 1st year MBA GPA at KUSB.

Once you decide on the best model to predict 1st year MBA GPA at KUSB, determine the cutoff to be used by the admissions committee to offer admissions for new applicants (i.e. students with a score above the cutoff would be admitted and those below (or equal to) the cutoff would not be admitted). This cutoff should be based on the regression model you created and should meet all of the target goals.

Keep in mind that you want theadmissionsguidelines to select the best students while still meeting the minimum enrollment of 100 studentsper year. To do so, you must account for the following in your target number of admitted students that will help determine what the cutoff should be...

• the data provided includestwo years'worth ofenrollmentdata
• not everyone that is admitted enrolls at the school. Typically, about 80% of admitted students enroll at the school.

After you determine your proposed cutoff, conduct an analysis on how many students were successful (i.e. MBA GPA > 3.2) but would not meet your new admissions criteria as well as how many students were not successful (i.e. MBA GPA < 3.2) but would meet your new admissions criteria (Hint: Think contingency table ).

As you can see from the table above, the Enrollment:Admission ratio ("E:A Ratio") ranged from 79-85% over the last 5 years (average ~82%). How would your proposed admission cutoff change if the yield was not 80%? For this question, you can use the following table to guide your analysis. I partially completed one row for you. With 80% typical yield and requirement of 100 students per year, the target number for admission is 250 [(2*100)/0.80]. The proposed cutoff should allow the admissions office to admit the top 250 students from this dataset. You determine this cutoff based on their predicted MBA GPA score when you apply your regression model to each student.

Yield E:A Ratio	Target # for Enrollment (100/yr for 2 years)	Target # for Admission (round up to nearest whole number)	Proposed Predicted MBA GPA Cutoff to meet Target # for Admission (value to 4 decimal points)
79%
80% (Typical)	200	250
81%
82%
83%
84%
85%

Your writeup should follow the same format as all other cases you have submitted during the semester. No more than 2 pages and should have an Executive Summary, Data Analysis and Recommendations section. All tables, charts, and figures should be properly labeled and cited in the text.

At a minimum, your report should include:

• Descriptive statistics as well as a discussion of current success rate for KUSB 1st year MBA students over the past 2 years at KUSB.
• Regression equation for KUSB to use to predict each applicant's KUSB 1st year MBA GPA based on the independent variables you think should be included.
• Description of the overall fit of your model using the usual descriptors we use to describe the goodness of fit of regression models.
• Cutoff that KUSB will use to determine whether a student is admitted (i.e. if predicted GPA MBA score is above this proposed cutoff, the student will be offered admission) using the typical E:A ratio of 80%. This cutoff should meet all the goals stated in the case.
• Analysis of the incorrect predictions. In other words, how many students attending KUSB over the past two years
  • would have been admitted under new admissions criteria but were "unsuccessful" (MBA GPA < 3.2), and
  • would not have been admitted under new admissions criteria but were "successful" (MBA GPA > 3.2)
• Analysis of the benefits of your new admissions criteria.
• Analysis of any downsides of your new admission criteria (think tradeoffs).
• Analysis of how this admissions cutoff would vary based on the expected Enrollment: Admission ratio (see table above). This will allow KUSB the flexibility to determine which cutoff they will use based on their prediction of the E:A ratio.
• Discussion of the limitations of the data as well as any future recommendations
  • always keep in mind your sampling and variables used to create your admissions criteria when you consider the limitations of your analysis- for example, in the Easton case, the data only represented 4 months of sales during an economic downturn so may not be generalizable to other months of the year or to better times). Consider limitations of using 1st year MBA GPA to determine admissions criteria. What additional variable(s), not currently included, would you recommend KUSB to consider adding in the future to improve their admissions model (include the type of variable as well as how you would code it).

This assignment is a group project. Please note that if there is something that you do not understand, you should email me for clarification. However, I am unable to perform your analysis for you or instruct you on what specific analytical steps to take.

Please submit the following files with your assigment:

1. 2 page Memorandum (PDF format)
2. Excel spreadsheet (1 per group that was used to inform yur report)

When you submit your assignment, you will need to answer supplemental questions at that time regarding the assignment. Your assignment will not be considered complete without answering these questions. You have a full week to complete this analysis and writeup. Please do not leave it until the last minute. Because of this flexibility and registrar requirements for grade submissions, there are no extensions. This exam (writeup and supplemental questions) must be completed to receive a grade in the class. You must also complete the last team dynamics survey.

Data Description

The data for the KUSB MBA admissions case is contained in the attached file.The file contains data for the 404 students who completed their first year in the KUSB MBA program over the past two years.The variables are coded as shown below.

Variable	Coding
ID	Student identification number
KUSB GPA	Grade point average for the 1st year of courses in the KUSB MBA program
GMAT	Score on the GMAT test
UG GPA	Undergraduate GPA
UG MAJ	Undergraduate Major 1: Business 2: STEM 3: Other
UG RAT	Rating of the UG School attended 5: UG School rated in top 20% of schools 4: UG School rated in second 20% 3: UG School rated in third 20% 2: UG School rated in fourth 20% 1: UG School rated in bottom 20%
AGE	Age of the student (years)
INT	0=US citizen, 1=International student