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Nordstokke, David W.; Colp, S. Mitchell – Practical Assessment, Research & Evaluation, 2018
Often, when testing for shift in location, researchers will utilize nonparametric statistical tests in place of their parametric counterparts when there is evidence or belief that the assumptions of the parametric test are not met (i.e., normally distributed dependent variables). An underlying and often unattended to assumption of nonparametric…
Descriptors: Nonparametric Statistics, Statistical Analysis, Monte Carlo Methods, Sample Size
de Winter, J. C .F. – Practical Assessment, Research & Evaluation, 2013
Researchers occasionally have to work with an extremely small sample size, defined herein as "N" less than or equal to 5. Some methodologists have cautioned against using the "t"-test when the sample size is extremely small, whereas others have suggested that using the "t"-test is feasible in such a case. The present…
Descriptors: Sample Size, Statistical Analysis, Hypothesis Testing, Simulation
Derryberry, DeWayne R.; Schou, Sue B.; Conover, W. J. – Journal of Statistics Education, 2010
Students learn to examine the distributional assumptions implicit in the usual t-tests and associated confidence intervals, but are rarely shown what to do when those assumptions are grossly violated. Three data sets are presented. Each data set involves a different distributional anomaly and each illustrates the use of a different nonparametric…
Descriptors: Nonparametric Statistics, Hypothesis Testing, Instruction, Statistical Distributions
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
Bennett, Richard P. – 1983
The results of a study of find alternative techniques for testing distributional normality are presented. A group of statistical techniques--some established and some new--were compared using empirical techniques. One new technique which appears to have higher power than the Lilliefors test was subjected to a better definition. Distributions under…
Descriptors: Comparative Analysis, Hypothesis Testing, Power (Statistics), Sample Size

Blair, R. Clifford; Higgins, James J. – Journal of Educational Statistics, 1985
This study was concerned with the effects of reliability of observations, sample size, magnitudes of treatment effects, and the shape of the sampled population on the relative power of the paired samples rank transform statistic and Wilcoxon's signed ranks statistic. (Author/LMO)
Descriptors: Effect Size, Hypothesis Testing, Power (Statistics), Reliability
Bonett, Douglas G. – Applied Psychological Measurement, 2006
Comparing variability of test scores across alternate forms, test conditions, or subpopulations is a fundamental problem in psychometrics. A confidence interval for a ratio of standard deviations is proposed that performs as well as the classic method with normal distributions and performs dramatically better with nonnormal distributions. A simple…
Descriptors: Intervals, Mathematical Concepts, Comparative Analysis, Psychometrics
Kromrey, Jeffrey D.; Blair, R. Clifford – 1991
New multivariate permutation tests are proposed that may be effectively substituted for Hotelling's T-Square test in situations commonly arising in educational research. The new tests: (1) are distribution-free; (2) provide tests of directional as well as non-directional hypotheses; (3) may be tailored for sensitivity to specific treatment…
Descriptors: Educational Research, Equations (Mathematics), Hypothesis Testing, Mathematical Models

Becker, Betsy Jane – Journal of Educational Statistics, 1991
The observed probability "p" is the social scientist's primary tool for evaluating the outcome of statistical hypothesis tests. The small-sample accuracy of nonnull asymptotic distributions of several functions of "p" was studied. Implications for use of the approximations are discussed. (SLD)
Descriptors: Equations (Mathematics), Estimation (Mathematics), Hypothesis Testing, Mathematical Models

Wilcox, Rand R. – Psychometrika, 1993
Modifications are proposed to the recently developed method of comparing one-step M-estimators of location corresponding to two independent groups that provides good control over the probability of Type I error even for unequal sample size, unequal variances, and different shaped distributions. Simulation results reveal cautions required. (SLD)
Descriptors: Comparative Analysis, Computer Simulation, Equations (Mathematics), Estimation (Mathematics)

Wilcox, Rand R.; Charlin, Ventura L. – Journal of Educational Statistics, 1986
This paper investigates three methods for comparing medians rather than means in studying two independent treatment groups. The method that gave the best results is based on a normal approximation of the distribution of the sample median where the variance is estimated using results reported by Maritz and Jarrett. (Author/JAZ)
Descriptors: Comparative Analysis, Computer Simulation, Computer Software, Equations (Mathematics)

Woodruff, David J.; Feldt, Leonard S. – Psychometrika, 1986
This paper presents 11 statistical procedures which test the equality of m coefficient alphas when the sample alpha coefficients are dependent. Several of the procedures are derived in detail, and numerical examples are given for two. (Author/LMO)
Descriptors: Analysis of Covariance, Analysis of Variance, Computer Simulation, Hypothesis Testing