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Gibbs, Benjamin G.; Shafer, Kevin; Miles, Aaron – International Journal of Research & Method in Education, 2017
While the use of inferential statistics is a nearly universal practice in the social sciences, there are instances where its application is unnecessary and potentially misleading. This is true for a portion of research using administrative data in educational research in the United States. Surveying all research articles using administrative data…
Descriptors: Statistical Inference, Statistics, Data, Information Utilization
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Bass, Roger F. – Psychology in the Schools, 1987
Evaluates arguments concerning the generality and statistical analysis of single-subject data. Considers the role of philosophy of science in evaluating research methodology. Single-subject data have special relevance for psychologists and educators who focus on the individual but statistical techniques for analyzing data have numerous…
Descriptors: Data Interpretation, Generalizability Theory, Generalization, Philosophy
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Vacha-Haase, Tammi; Nilsson, Johanna E. – Measurement and Evaluation in Counseling and Development, 1998
Statistical significance reporting and use in educational and psychological research is reviewed. An assessment of the use of statistical significance in articles published in MECD from 1990-1996 is presented. The elements of statistical significance (including sample size, effect size, and power), interpretation of results, common erroneous…
Descriptors: Data Interpretation, Educational Research, Hypothesis Testing, Measurement
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Knapp, Thomas R. – Mid-Western Educational Researcher, 1999
Presents an opinion on the appropriate use of significance tests, especially in the context of regression analysis, the most commonly encountered statistical technique in education and related disciplines. Briefly discusses the appropriate use of power analysis. Contains 47 references. (Author/SV)
Descriptors: Data Interpretation, Educational Research, Effect Size, Hypothesis Testing
Thompson, Bruce – 1987
This paper evaluates the logic underlying various criticisms of statistical significance testing and makes specific recommendations for scientific and editorial practice that might better increase the knowledge base. Reliance on the traditional hypothesis testing model has led to a major bias against nonsignificant results and to misinterpretation…
Descriptors: Analysis of Variance, Data Interpretation, Editors, Effect Size