As usual, you have a homework case. This week, we're back to Holmes University, working on a freshmen retention task force. We will build a model to predict whether students will return for their...

1 answer below »
As usual, you have a homework case. This week, we're back to Holmes University, working on a freshmen retention task force. We will build a model to predict whether students will return for their sophomore year, and consider how to use the model to decide which students will receive a costly intervention.


We're back to Holmes University this week. We're on a freshmen retention task force, trying to identify freshmen who are likely to leave Holmes University, i.e. not return for their sophomore year.We've collected the following variables:GPA: The student's GPA in their freshman yearAthlete: =1 if the student is an athlete, =0 otherwiseMiles from home: Distance from campus to the student's homeCollege: College in which the student is enrolled: Education, Business, or Arts and SciencesAccommodations: Home or DormWork Hours: The number of hours the student said they worked at a job during the last week. They could either answer 0, 0-5, 5-10, 10-15, 15-20, or 20+; this has been coded with the midpoint of that range, or 22.5 for 20+. Not perfect, but it's the best we have.Attends office hours: How often does the student say they go to office hours: Never, Sometimes, or RegularlyHS GPA: The student's high school GPAReturn: Dependent variable; =1 if the student returned, =0 if the student did not return.Your sample includes 500 students; of those, 395 return, and 105 do not.


Build a logistic regression model to predict which students will leave/return to Holmes University for their sophomore year.In addition to the variables given, consider polynomial and cross-product terms.Particularly, it looks like GPA, College, and Miles from home are important variables; a polynomial or cross-product involving those variables is useful.Interpret the parameter estimates in your model, including numerical effects or graphical display of effects.What generally makes students more or less likely to leave Holmes University?The retention task force plans to use your model to identify students who are likely to leave. It will place them in a program where they get access to additional services and possibly a small financial incentive to return. The cost of this program is $1,000 per student you identify as likely to leave. Every student who you correctly identify as likely to leave will now be more likely to return: correctly identifying a student as likely to leave gains $4,000 per student.What cutoff probability should you use to identify likely leavers?How much net benefit will this program give the university, based on the 500 students in your sample?Write findings in a case report as usual, and submit it by 11:59pm on Sunday.


https://docs.google.com/spreadsheets/d/1A17gTDA_EK3NN11IHc0d2o20EKu3d_-oE1cFtjig0Ro/edit?usp=sharing
Answered 13 days AfterJun 20, 2022

Answer To: As usual, you have a homework case. This week, we're back to Holmes University, working on a...

Shakeel answered on Jul 03 2022
80 Votes
Introduction
In this paper, it is tried to figure out which factors significantly affect the return of freshmen to their sophomore year of Holmes University. The sample data on freshmen retention taskforce is collected on
certain variables like their GPA, their status as an Athlete, Distance from the college, College in which they are enrolled, Their accommodation, work hours, office hours, HS GPA and their intention of return or not. The size of sample is taken as 500.
Here, we use the Logistic regression to build a model to predict whether students will return for their sophomore year, and use the model to decide which students will receive a costly intervention. The analysis is carried on in the SPSS Ver.17 software and the results are interpreted, discussed and presented in report format,
Data
The data collected from 500 student on different parameters are taken and their descriptive statistics are presented here for understanding on their distribution and point estimates.
Graph 1 shows the number of students who return sophomore year.
Graph 1: Return for sophomore year
Around 79% students return for their sophomore years while rest of 21% don’t. Hence, large numbers of students are retained to the university.
Graph 2 shows the number of students who are athlete.
Graph 2: Number of Athletes
Around 36% students are athlete while rest of 64% are not.
Graph 3 shows the number of students in different colleges.
Graph 3: Students in colleges
The highest number of students belong to A&S college (241), followed by Business (133) and Education (126).
Graph 4 shows the number of students across the type of accommodations.
Graph 4: Accommodation
Dorm is highly used by student where it is engaged by 422 students out of 500. Students come from home are small in numbers and here, they are only 78.
Graph 5 shows the “Attended office hours” by the students.
Graph 5: Attended office hours.
Only 55 students attend office hours regularly while 96 students attend sometimes. A large number of students don’t attend office and their numbers are as high as 349.
Table 1 shows the Mean, Min and Max value of the variables – GPA, Miles from home, Work hours and HS GPA.
Table 1: Mean, Min and...
SOLUTION.PDF

Answer To This Question Is Available To Download

Related Questions & Answers

More Questions »

Submit New Assignment

Copy and Paste Your Assignment Here