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Newman, Isadore; And Others – 1980
When investigating differences between two sets of scores, the t test is appropriate. If the two sets of data are from two groups of subjects, then the independent t test is appropriate. If the two sets are from the same subjects, the dependent t test is required. In this paper, the authors describe the use of a third test when part of a data set…
Descriptors: Hypothesis Testing, Mathematical Models, Multiple Regression Analysis, Research Design
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Preacher, Kristopher J.; Curran, Patrick J.; Bauer, Daniel J. – Journal of Educational and Behavioral Statistics, 2006
Simple slopes, regions of significance, and confidence bands are commonly used to evaluate interactions in multiple linear regression (MLR) models, and the use of these techniques has recently been extended to multilevel or hierarchical linear modeling (HLM) and latent curve analysis (LCA). However, conducting these tests and plotting the…
Descriptors: Interaction, Multiple Regression Analysis, Computation, Instrumentation
Witmer, David R. – 1979
A search for better predictors of incomes of high school and college graduates is described. The accuracy of the prediction, implicit in the work of John R. Walsh of Harvard University, that the income differences in a given year are good indicators of income differences in future years, was tested by applying standard statistical procedures to…
Descriptors: College Graduates, Conference Reports, Economic Status, High School Graduates
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Campbell, S. Duke; Greenberg, Barry – 1979
The development of a predictive equation capable of explaining a significant percentage of enrollment variability at Florida International University is described. A model utilizing trend analysis and a multiple regression approach to enrollment forecasting was adapted to investigate enrollment dynamics at the university. Four independent…
Descriptors: College Planning, Conference Reports, Economic Factors, Enrollment Projections