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Rosenthal, James A. – Springer, 2011
Written by a social worker for social work students, this is a nuts and bolts guide to statistics that presents complex calculations and concepts in clear, easy-to-understand language. It includes numerous examples, data sets, and issues that students will encounter in social work practice. The first section introduces basic concepts and terms to…
Descriptors: Statistics, Data Interpretation, Social Work, Social Science Research

Eiting, Mindert H.; Mellenbergh, Gideon J. – Multivariate Behavioral Research, 1981
A commentary is made on a previously published article concerning testing the equivalence of covariance matrices. An error in the previous article (by the same authors) is pointed out and the consequences of the error are discussed. (JKS)
Descriptors: Analysis of Covariance, Data Analysis, Hypothesis Testing, Matrices

Busk, Patricia L.; Marascuilo, Leonard A. – Australian Journal of Education, 1989
An extension of the discussion of loglinear models presents post hoc procedures for statistically evaluating treatment effects, contrasts, and confidence intervals, illustrating methods for main effect and interaction contrasts and paying special attention to odds ratios and their interval estimates. Procedures for treating variables as…
Descriptors: Estimation (Mathematics), Hypothesis Testing, Interaction, Mathematical Models

Brainerd, Charles J. – Contemporary Educational Psychology, 1982
According to the stage-learning hypothesis, children's ability to learn is constrained by their pretraining stages of cognitive development. Some procedures for obtaining unconfounded tests of this hypothesis are developed in this paper, and some applications to factorial experiments are considered. (Author/BW)
Descriptors: Cognitive Development, Developmental Stages, Elementary Education, Hypothesis Testing

Yancey, Bernard D. – New Directions for Institutional Research, 1988
The ultimate goal of the institutional researcher is not always to test a research hypothesis, but more often simply to find an appropriate model to gain an understanding of the underlying characteristics and interrelationships of the data. Exploratory data analysis provides a means of accomplishing this. (Author)
Descriptors: Data Interpretation, Higher Education, Hypothesis Testing, Institutional Research
Schmitt, Alicia P.; And Others – 1992
Studies evaluating hypotheses about sources of differential item functioning (DIF) are classified into two categories: observational studies evaluating operational items and randomized DIF studies evaluating specially constructed items. For observational studies, advice is given for item classification, sample selection, the matching criterion,…
Descriptors: Causal Models, Classification, Effect Size, Estimation (Mathematics)

Conquest, Loveday L. – Environmental Monitoring and Assessment, 1993
Presents two statistical topics and examples of their use in natural resource monitoring. The first topic deals with use of correlated observations in calculations of variance estimates for a regional mean, required sample size determination, and confidence intervals. The second topic concerns the use of Bayesian techniques in hypothesis testing.…
Descriptors: Bayesian Statistics, Environmental Education, Environmental Research, Evaluation Methods