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Peer reviewedBaker, Bruce D. – Economics of Education Review, 2001
Explores whether flexible nonlinear models (including neural networks and genetic algorithms) can reveal otherwise unexpected patterns of relationship in typical school-productivity data. Applying three types of algorithms alongside regression modeling to school-level data in 183 elementary schools proves the hypothesis and reveals new directions…
Descriptors: Algorithms, Elementary Education, Evaluation Methods, Mathematical Models
Peer reviewedOkunade, Albert Ade – Education Economics, 1993
Analyzes propensity of business school alumni to give cash donations to their alma mater. Estimates a utility maximization model, using logistic regression and survey sample data of 1956-90 graduates of a large U.S public research university. Giving probability is strongly correlated with specific majors, time since graduation, other factors.…
Descriptors: Alumni, Business Administration, Educational Economics, Fund Raising
Download full textBlankmeyer, Eric – 1993
Ordinary least-squares regression treats the variables asymmetrically, designating a dependent variable and one or more independent variables. When it is not obvious how to make this distinction, a researcher may prefer to use orthogonal regression, which treats the variables symmetrically. However, the usual procedure for orthogonal regression is…
Descriptors: Equations (Mathematics), Estimation (Mathematics), Least Squares Statistics, Mathematical Models
Peer reviewedBaker, Bruce D.; Richards, Craig E. – Economics of Education Review, 1999
Applies neural network methods for forecasting 1991-95 per-pupil expenditures in U.S. public elementary and secondary schools. Forecasting models included the National Center for Education Statistics' multivariate regression model and three neural architectures. Regarding prediction accuracy, neural network results were comparable or superior to…
Descriptors: Algorithms, Econometrics, Elementary Secondary Education, Expenditure per Student
Peer reviewedEhrenberg, Ronald G.; Hurst, Peter J. – Economics of Education Review, 1998
Describes how to employ multivariate regression models and National Research Council data (used to rank doctoral programs) to analyze how measures of program size, faculty seniority, and faculty research and doctoral-degree productivity influence subjective ratings of doctoral programs in 35 academic fields. Illustrates how to compute the effects…
Descriptors: College Faculty, Doctoral Programs, Economics Education, Higher Education
Ahmed, Susan – 1997
This working paper contains the overheads used in a seminar designed to introduce some basic concepts of statistics to nonstatisticians. The seminar has been presented on several occasions. The first part of the seminar, and the first set of overheads, deals with the essentials of statistics, including: (1) population, sample, and inference; (2)…
Descriptors: Correlation, Educational Policy, Educational Research, Mathematical Models
