Estimating New Freshmen Enrollment

1
Estimating New Freshmen Enrollment

• Agatha Awuah, Eric Kimmelman, Michael Dillon
• Office of Institutional Research
• Binghamton University
• AIRPO
• June 11-13, 2003

2
Admissions Process

• Set new freshmen targets.
• Make offers of admission.
• Build wait list.
• Collect deposits.
• Estimate enrollment based on deposits received.
• Make offers to the wait list if needed.

3
Previous Method

• Required to estimate enrollment
• Yieldlast years enrollment (1,000) divided by
  last years offers (3,000).
• Est. Yield1,000/3,000
• .33
• Target for current year (2,000).
• Est. Offers Needed2,000/.33
• 6,000

4
Previous Method-Results
5
Yield by SAT Score-Fall 2002
6
Logistic Regression

• Dichotomous dependent variable.
• Estimates conditional probability of enrollment
  controlling for multiple independent
  variables-yield.
• Available in most statistical packages.

7
The Data

• Five fall semesters -1998 to 2002.
• Only matric freshmen admits (35,796) included.
• Enrollment of admitted applicants 9,811.
• Yield rate (9,811/35,796)10027.4.

8
Steps to Building Model 1

• Estimate baseline model using 5 years of data
  (intercept only), estimate enrollment, then
  calculate absolute prediction error by semester.
• Add additional variables and calculate new
  absolute prediction error.

9
Steps to Building Model 2

• Compare prediction errors. If the second
  prediction error is smaller than the first, keep
  new variable in the model. If not, drop it from
  the model.
• Continue process until smallest possible
  prediction error is attained.
• Predict enrollment for each year in the sample
  with data from other 4 years.

10
Step One-Baseline Model
11
Step Two-Add SAT and HS Avg. 1
12
Step Two-Add SAT and HS Avg. 2
13
Step Two-Add SAT and HS Avg. 3
14
Full Model 1-Academics
15
Full Model 2-Inqs/Demo
16
Full Model 3-Inst.
17
Full Model Performance
18
Full Model Evaluation
19
Estimating Quality of Regular Admits Fall 2002
20
Additional Applications

• Predict retention.
• Identify Hot Prospects.
• Identify potential donors.
• Evaluate recruitment efforts.

21
Logistic Regression

• Berge, D.A. Hendel, D.D. (2003, Winter).
  Using Logistic Regression to Guide Enrollment
  Management at a Public Regional University. AIR
  Professional File, 1-11.
• Thomas, E, Dawes, W. Reznik, G. (2001,
  Winter). Using Predictive Modeling to Target
  Student Recruitment Theory and Practice. AIR
  Professional File, 1-8.
• Aldrich, J.H. Nelson, F.D. (1984). Linear
  Probability, Logit and Probit Models. Sage
  University Papers Quantitative Applications in
  the Social Sciences, 07-045. Newbury Park, CA
  Sage Publications

22
Estimating New Freshmen Enrollment

• Agatha Awuah, Eric Kimmelman, Michael Dillon
• Office of Institutional Research
• Binghamton University
• AIRPO
• June 11-13, 2003
• Website http//buoir.binghamton.edu