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Osborne, Jason W. – Practical Assessment, Research & Evaluation, 2013
Osborne and Waters (2002) focused on checking some of the assumptions of multiple linear regression. In a critique of that paper, Williams, Grajales, and Kurkiewicz correctly clarify that regression models estimated using ordinary least squares require the assumption of normally distributed errors, but not the assumption of normally distributed…
Descriptors: Multiple Regression Analysis, Least Squares Statistics, Computation, Statistical Analysis
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Hayton, James C. – Multivariate Behavioral Research, 2009
In the article "Exploring the Sensitivity of Horn's Parallel Analysis to the Distributional Form of Random Data," Dinno (this issue) provides strong evidence that the distribution of random data does not have a significant influence on the outcome of the analysis. Hayton appreciates the thorough approach to evaluating this assumption, and agrees…
Descriptors: Research Methodology, Statistical Distributions, Evaluation, Statistical Analysis
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Desmet, Charlotte; Poulin-Charronnat, Benedicte; Lalitte, Philippe; Perruchet, Pierre – Journal of Experimental Psychology: Learning, Memory, and Cognition, 2009
In a recent study, G. Kuhn and Z. Dienes (2005) reported that participants previously exposed to a set of musical tunes generated by a biconditional grammar subsequently preferred new tunes that respected the grammar over new ungrammatical tunes. Because the study and test tunes did not share any chunks of adjacent intervals, this result may be…
Descriptors: Intervals, Statistical Distributions, Statistical Analysis, Probability
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Gorard, Stephen – British Journal of Educational Studies, 2005
This paper discusses the reliance of numerical analysis on the concept of the standard deviation, and its close relative the variance. It suggests that the original reasons why the standard deviation concept has permeated traditional statistics are no longer clearly valid, if they ever were. The absolute mean deviation, it is argued here, has many…
Descriptors: Statistics, Statistical Analysis, Evaluation Methods, Statistical Distributions
Geisser, Seymour – 1985
This document reviews "The Collected Works of George E. P. Box," edited by G. C. Tiao. The two-volume collection is divided into five parts. Each part is prefaced with an introduction by a statistical researcher giving his view of the motivation and highlights of the papers presented. The 16 papers in Part 1 on statistical inference,…
Descriptors: Adults, Psychometrics, Research Methodology, Researchers
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Krishnan, Parmeswara – Alberta Journal of Educational Research, 1995
Comments on some methodological limitations of the research base of "The Bell Curve": blind use of the normal distribution (bell curve); avoidance of nonnormal statistical distributions, which are more appropriate for some social and economic characteristics; copious use of percentiles and quintiles, inappropriate with nonnormal…
Descriptors: Data Interpretation, Intelligence Quotient, Multivariate Analysis, Research Methodology
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Tang, S. M.; MacNeill, I. B. – Environmental Monitoring and Assessment, 1992
The problem of monitoring trends for changes at unknown times is considered. Statistics that permit one to focus high power on a segment of the monitored period are studied. Numerical procedures are developed to compute the null distribution of these statistics. (Author)
Descriptors: Air Pollution, Environmental Education, Mathematical Formulas, Measurement Techniques
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Huberty, Carl J. – Educational Researcher, 1987
Two approaches of statistical testing are critically reviewed. A new approach, which is a hybrid of the two, is proposed. The new approach requires the researcher to think about the two types of potential inferential errors and an explicit alternative hypothesis of interest. (VM)
Descriptors: Educational Assessment, Instruction, Multivariate Analysis, Researchers