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Question and sample writeup and data in document

 

this assignment involves developing an admissions model for the Kurtosis University Business School (KUSB) MBA program. The goal is to predict the first-year GPA of MBA students based on several independent variables provided from student data over the past two years. The specific tasks include:

 

Data Analysis: Examine and analyze the provided data to understand the characteristics and performance of current and past MBA students. This involves computing descriptive statistics and fitting a regression model.

Regression Modeling: Build a linear regression model using predictors such as GMAT scores, undergraduate GPA, major, age, and other factors to predict students’ first-year MBA GPA.

Determine Admission Cutoff: Use the regression model to identify a GPA cutoff that would allow KUSB to admit the top 250 students, ensuring a balance between high academic standards and sufficient enrollment figures, given the historical enrollment-to-admission ratio of 80%.

Contingency Analysis: Evaluate the impact of the new cutoff on student success rates by determining how many students meeting this cutoff would be expected to succeed (i.e., achieve a first-year MBA GPA greater than 3.2) or not meet these standards.

Model Evaluation and Recommendations: Assess the model’s fit and predictive power and discuss the implications, limitations, and potential improvements to the admissions process.

The end goal is to assist the MBA program in refining their admissions criteria to enhance student selection while achieving strategic enrollment goals.

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