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Showing 1 to 15 of 21 results Save | Export
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Kim, Yukyoum; Lee, J. Lucy – Measurement in Physical Education and Exercise Science, 2019
The purposes of this manuscript are to identify common statistical mistakes in sport management, and to provide scholars with suggestions on how to develop and improve the quality of quantitative research. We have reviewed articles published from 2001 to 2017 in the "Journal of Sport Management," "Sport Management Review,"…
Descriptors: Athletics, Research, Research Problems, Statistical Analysis
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Gorard, Stephen; Gorard, Jonathan – International Journal of Social Research Methodology, 2016
This brief paper introduces a new approach to assessing the trustworthiness of research comparisons when expressed numerically. The 'number needed to disturb' a research finding would be the number of counterfactual values that can be added to the smallest arm of any comparison before the difference or 'effect' size disappears, minus the number of…
Descriptors: Statistical Significance, Testing, Sampling, Attrition (Research Studies)
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Neale, Dave – Oxford Review of Education, 2015
Recently, Stephen Gorard has outlined strong objections to the use of significance testing in social research. He has argued, first, that as the samples used in social research are almost always non-random it is not possible to use inferential statistical techniques and, second, that even if a truly random sample were achieved, the logic behind…
Descriptors: Statistical Significance, Statistical Analysis, Sampling, Probability
Shaver, James P. – Phi Delta Kappan, 1985
A dialog between two fictional teachers provides some basic examples of how research that uses approved methodology may provide results that are significant statistically but not significant practically. (PGD)
Descriptors: Educational Research, Research Methodology, Research Problems, Sampling
Shaver, James P. – Phi Delta Kappan, 1985
The second half of a dialogue between two fictional teachers examines the significance of statistical significance in research and considers the factors affecting the extent to which research results provide important or useful information. (PGD)
Descriptors: Educational Research, Research Methodology, Research Problems, Sampling
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Hiller, Dana V.; Philliber, William W. – Journal of Marriage and the Family, 1985
A review of articles that report study results based on couple samples indicated response rates are rarely high enough for statistical inference. Four procedures that can be used to compensate for insufficient response rates (collecting information from nonparticipants, census comparisons, adjustment in analysis, and replication) are examined.…
Descriptors: Generalization, Influences, Research Problems, Sample Size
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Hsu, Tse-Chi; Sebatane, E. Molapi – Journal of Experimental Education, 1979
A Monte Carlo technique was used to investigate the effect of the differences in covariate means among treatment groups on the significance level and the power of the F-test of the analysis of covariance. (Author/GDC)
Descriptors: Analysis of Covariance, Correlation, Research Design, Research Problems
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Lissitz, Robert W.; Chardos, Steve – Educational and Psychological Measurement, 1975
Describes some of the situations in which a psychologist is likely to violate the assumption of independent errors. A Monte-Carlo study of the effects of this violation is then described. (Author/RC)
Descriptors: Analysis of Variance, Computer Programs, Hypothesis Testing, Matrices
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Hedges, Larry V. – Journal of Educational Statistics, 1984
If the quantitative result of a study is observed only when the mean difference is statistically significant, the observed mean difference, variance, and effect size are biased estimators of corresponding population parameters. The exact distribution of sample effect size and the maximum likelihood estimator of effect size are derived. (Author/BW)
Descriptors: Effect Size, Estimation (Mathematics), Maximum Likelihood Statistics, Meta Analysis
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Carver, Ronald P. – Journal of Experimental Education, 1993
Four things are recommended to minimize the influence or importance of statistical significance testing. Researchers must not neglect to add "statistical" to significant and could interpret results before giving p-values. Effect sizes should be reported with measures of sampling error, and replication can be built into the design. (SLD)
Descriptors: Educational Researchers, Effect Size, Error of Measurement, Research Methodology
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Carroll, Robert M.; Nordholm, Lena A. – Educational and Psychological Measurement, 1975
Statistics used to estimate the population correlation ratio were reviewed and evaluated. The sampling distributions of Kelly's and Hays' statistics were studied empirically by computer simulation within the context of a three level one-way fixed effects analysis of variance design. (Author/RC)
Descriptors: Analysis of Variance, Bias, Comparative Analysis, Correlation
Thompson, Bruce – 1992
Three criticisms of overreliance on results from statistical significance tests are noted. It is suggested that: (1) statistical significance tests are often tautological; (2) some uses can involve comparisons that are not completely sensible; and (3) using statistical significance tests to evaluate both methodological assumptions (e.g., the…
Descriptors: Effect Size, Estimation (Mathematics), Evaluation Methods, Regression (Statistics)
Franz, Jennifer D. – 1987
Two basic methods exist for drawing probability samples to be used in telephone surveys: directory sampling (from alphabetical or street directories) and random digit dialing (RDD). RDD includes unlisted numbers, whereas directory sampling includes only listed numbers. The goal of this paper is to estimate the effect of failure to include…
Descriptors: Bias, Community Surveys, Cost Effectiveness, Demography
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Hummel, Thomas J. – 1976
An investigation was conducted of the characteristics of two estimation procedures and corresponding test statistics used in the analysis of completely randomized factorial experiments when observations are lost at random. For one estimator, contrast coefficients for cell means did not involve the cell frequencies. For the other, contrast…
Descriptors: Data Analysis, Hypothesis Testing, Measurement Techniques, Observation
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Ross, Kenneth N. – Journal of Educational Statistics, 1979
It is shown that using formulae for the estimation of sampling errors based on simple random sampling, when a design actually involves cluster sampling, can lead to serious underestimation of error. Jackknife and balanced repeated replication are recommended as techniques for dealing with this problem. (Author/CTM)
Descriptors: Foreign Countries, Hypothesis Testing, Research Design, Research Problems
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