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Showing 1 to 15 of 38 results Save | Export
Clintin P. Davis-Stober; Jason Dana; David Kellen; Sara D. McMullin; Wes Bonifay – Grantee Submission, 2023
Conducting research with human subjects can be difficult because of limited sample sizes and small empirical effects. We demonstrate that this problem can yield patterns of results that are practically indistinguishable from flipping a coin to determine the direction of treatment effects. We use this idea of random conclusions to establish a…
Descriptors: Research Methodology, Sample Size, Effect Size, Hypothesis Testing
Sun-Joo Cho; Amanda Goodwin; Matthew Naveiras; Paul De Boeck – Grantee Submission, 2024
Explanatory item response models (EIRMs) have been applied to investigate the effects of person covariates, item covariates, and their interactions in the fields of reading education and psycholinguistics. In practice, it is often assumed that the relationships between the covariates and the logit transformation of item response probability are…
Descriptors: Item Response Theory, Test Items, Models, Maximum Likelihood Statistics
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Sun-Joo Cho; Amanda Goodwin; Matthew Naveiras; Paul De Boeck – Journal of Educational Measurement, 2024
Explanatory item response models (EIRMs) have been applied to investigate the effects of person covariates, item covariates, and their interactions in the fields of reading education and psycholinguistics. In practice, it is often assumed that the relationships between the covariates and the logit transformation of item response probability are…
Descriptors: Item Response Theory, Test Items, Models, Maximum Likelihood Statistics
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Segal, Ruti; Stupel, Moshe – International Electronic Journal of Mathematics Education, 2023
The benefits of technological and theoretical scaffolding were observed when pre-service teachers aiming to teach upper elementary grades were given three learning-based geometrical inquiry tasks involving inscribed circles. They were asked to collaboratively examine the accompanying geometrical illustration and data for some new or interesting…
Descriptors: Preservice Teachers, Mathematics Teachers, Mathematics Instruction, Mathematics Skills
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Suero, Manuel; Privado, Jesús; Botella, Juan – Psicologica: International Journal of Methodology and Experimental Psychology, 2017
A simulation study is presented to evaluate and compare three methods to estimate the variance of the estimates of the parameters d and "C" of the signal detection theory (SDT). Several methods have been proposed to calculate the variance of their estimators, "d'" and "c." Those methods have been mostly assessed by…
Descriptors: Evaluation Methods, Theories, Simulation, Statistical Analysis
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Longford, Nicholas T. – Journal of Educational and Behavioral Statistics, 2014
A method for medical screening is adapted to differential item functioning (DIF). Its essential elements are explicit declarations of the level of DIF that is acceptable and of the loss function that quantifies the consequences of the two kinds of inappropriate classification of an item. Instead of a single level and a single function, sets of…
Descriptors: Test Items, Test Bias, Simulation, Hypothesis Testing
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Zaidin, M. Arifin – Journal of Education and Practice, 2015
The purpose of this study is to assess the correlation between aspects of tutor and the students' basic writing outcomes of the Elementary School Teacher Education at the Distance Learning Program Unit, Open University of Palu. This is ex post facto correlation with the population research of 387 people and the total sample of 100 people. This…
Descriptors: Tutors, Writing Ability, Correlation, Distance Education
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Holland, Bart K. – Teaching Statistics: An International Journal for Teachers, 2011
Distributions are the basis for an enormous amount of theoretical and applied work in statistics. While there are formal definitions of distributions and many formulas to characterize them, it is important that students at first get a clear introduction to this basic concept. For many of them, neither words nor formulas can match the power of a…
Descriptors: Hypothesis Testing, Probability, Statistics, College Mathematics
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Osler, James Edward; Mansaray, Mahmud A. – Journal of Educational Technology, 2013
The online deployment of Technology Engineered online Student Ratings of Instruction (SRIs) by colleges and universities in the United States has dynamically changed the deployment of course evaluation. This research investigation is the fourth part of a post hoc study that analytically and psychometrically examines the design, reliability, and…
Descriptors: Course Evaluation, Educational Technology, Black Colleges, Higher Education
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Martin, Charles G.; Games, Paul A. – Journal of Experimental Education, 1981
Power and stability of Type I error rates are investigated for the Box-Scheffe test of homogeneity of variance with varying subsample sizes under conditions of normality and nonnormality. The test is shown to be robust to violation of the normality assumption when sampling is from a leptokurtic population. (Author/GK)
Descriptors: Hypothesis Testing, Mathematical Formulas, Statistical Analysis
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Willson, Victor L. – Educational and Psychological Measurement, 1980
Guilford's average interrater correlation coefficient is shown to be related to the Friedman Rank Sum statistic. Under the null hypothesis of zero correlation, the resultant distribution is known and the hypothesis can be tested. Large sample and tied score cases are also considered. An example from Guilford (1954) is presented. (Author)
Descriptors: Correlation, Hypothesis Testing, Mathematical Formulas, Reliability
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Morrow, James R.; Hopkins, Kenneth D. – Journal of Experimental Education, 1979
The F-distribution approximation suggested by Dixon was investigated at various combinations of alpha and degrees of freedom. Tabled values were compared with values computed utilizing the suggested formula. (Author/GSK)
Descriptors: Hypothesis Testing, Mathematical Formulas, Statistical Analysis
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Wilcox, Rand R. – Educational and Psychological Measurement, 1983
When comparing k normal populations an investigator might want to know the probability that the population with the largest population mean will have the largest sample mean. This paper describes and illustrates methods of approximating this probability when the variances are unknown and possibly unequal. (Author/BW)
Descriptors: Data Analysis, Hypothesis Testing, Mathematical Formulas, Probability
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Lutz, J. Gary; Cundari, Leigh A. – Journal of Educational Statistics, 1989
Means of identifying sources of rejection of hypotheses regarding linear multivariate statistical models are discussed. Problems with the use of a global test using Roy's largest root criterion and means of solving them are presented, along with a practical application of the techniques. (TJH)
Descriptors: Hypothesis Testing, Mathematical Formulas, Mathematical Models, Multivariate Analysis
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
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