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Kasprowicz, Tomasz; Musumeci, Jim – Journal of Statistics Education, 2015
One econometric rule of thumb is that greater dispersion in observations of the independent variable improves estimates of regression coefficients and therefore produces better results, i.e., lower standard errors of the estimates. Nevertheless, students often seem to mistrust precisely the observations that contribute the most to this greater…
Descriptors: Regression (Statistics), Teaching Methods, Active Learning, Observation
Afshartous, David; Preston, Richard A. – Journal of Statistics Education, 2011
We consider the effect on estimation of simultaneous variable centering and interaction effects in linear regression. We technically define, review, and amplify many of the statistical issues for interaction models with centering in order to create a useful and compact reference for teachers, students, and applied researchers. In addition, we…
Descriptors: Interaction, Regression (Statistics), Computation, Research Methodology
Actuarial Foundation, 2012
The purpose of these modules is to provide an introduction to the world of probability and statistics to accelerated mathematics students at the high school level. The materials are centered on the fictional town of Happy Shores, a coastal community which is at risk for hurricanes. Actuaries at an insurance company figure out the risks and…
Descriptors: Mathematical Concepts, Probability, Statistics, Learning Modules
DeMartini, Kelly S.; Carey, Kate B. – Journal of American College Health, 2009
Objective: The current study identified gender-specific correlates of hazardous drinker status as defined by the AUDIT. Participants: A total of 462 college student volunteers completed the study in 2006. The sample was predominantly Caucasian (75%) and female (55%). Methods: Participants completed a survey assessing demographics, alcohol use…
Descriptors: College Students, Gender Differences, Screening Tests, Correlation
Bickel, Robert – Guilford Publications, 2007
This book provides a uniquely accessible introduction to multilevel modeling, a powerful tool for analyzing relationships between an individual level dependent variable, such as student reading achievement, and individual-level and contextual explanatory factors, such as gender and neighborhood quality. Helping readers build on the statistical…
Descriptors: Regression (Statistics), Social Sciences, Statistical Analysis, Structural Equation Models
Rots, Isabel; Aelterman, Antonia – Educational Studies, 2008
This study focuses on the relationship between teacher education and graduates' intended and actual entrance into teaching. Moreover, it explores how this relationship differs for two types of initial teacher training for secondary education. A hypothetical model of graduates' entrance into the teaching profession comprising empirically grounded…
Descriptors: Teaching (Occupation), Labor Market, Graduates, Intention
O'Brien, Francis J., Jr. – 1987
This paper is part of a series of applied statistics monographs intended to provide supplementary reading for applied statistics students. In the present paper, derivations of the unbiased standard error of estimate for both the raw score and standard score linear models are presented. The derivations for raw score linear models are presented in…
Descriptors: Error of Measurement, Estimation (Mathematics), Goodness of Fit, Higher Education

Lottes, Ilsa L.; And Others – Teaching Sociology, 1996
Defines and illustrates basic concepts of dichotomous logistic regression (DLR) and presents strategies for teaching these concepts. Strategies include using analogies between ordinary least squares regression and logistic regression; illustrating concepts with contingency tables; and linking logistic regression concepts to interpretation of…
Descriptors: Analysis of Variance, Causal Models, Higher Education, Instructional Improvement