Estimating Errors in Student Enrollment Forecasting.

Abstract

The purpose of this paper is to demonstrate how longitudinal data can be used to determine variances, and hence confidence bounds, on student enrollment forecasts in addition to finding the forecasts themselves. The cases of known admission numbers and unknown admission numbers, but with an assumed Poisson distribution, are both considered. The model takes into account different admissions at fall and spring semesters, and also allows for differences in the continuation fractions for these different semesters. Normal approximations are used to calculate the probability that a total enrollment lies in a given interval. Numerical examples illustrate the results. (Author)

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Document Details

Document Type
Technical Report
Publication Date
Jan 01, 1979
Accession Number
ADA070084

Entities

People

  • Kneale T. Marshall
  • Robert M. Oliver

Organizations

  • Naval Postgraduate School

Tags

DTIC Thesaurus Topics

  • Binomials
  • Business Administration
  • California
  • Delphi Method
  • Distribution Functions
  • Distribution Theory
  • Education
  • Equations
  • Intervals
  • Normal Distribution
  • Probability
  • Probability Distributions
  • Random Variables
  • Schools
  • Students
  • Uncertainty
  • Universities

Fields of Study

  • Mathematics

Readers

  • Computational Modeling and Simulation
  • Medical or Health Care Field.
  • Statistical inference.