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Walter M. Stroup; Anthony Petrosino; Corey Brady; Karen Duseau – North American Chapter of the International Group for the Psychology of Mathematics Education, 2023
Tests of statistical significance often play a decisive role in establishing the empirical warrant of evidence-based research in education. The results from pattern-based assessment items, as introduced in this paper, are categorical and multimodal and do not immediately support the use of measures of central tendency as typically related to…
Descriptors: Statistical Significance, Comparative Analysis, Research Methodology, Evaluation Methods
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Golino, Hudson F.; Gomes, Cristiano M. A. – International Journal of Research & Method in Education, 2016
This paper presents a non-parametric imputation technique, named random forest, from the machine learning field. The random forest procedure has two main tuning parameters: the number of trees grown in the prediction and the number of predictors used. Fifty experimental conditions were created in the imputation procedure, with different…
Descriptors: Item Response Theory, Regression (Statistics), Difficulty Level, Goodness of Fit
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Batdi, Veli; Elaldi, Senel – Journal of Education and Learning, 2016
The purpose of this study is to evaluate the views of German teacher trainers working in Turkey about their level regarding Reigeluth's organizational strategies and to analyze their views in terms of gender, geographic region, seniority, and graduated high school variables. While the population of the study consisted of German teacher trainers…
Descriptors: Teacher Educators, Content Validity, Instructional Design, Likert Scales
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
Toothaker, Larry E. – 1971
Various cases of unequal variances and unequal sample sizes from a normal and a skewed population were used to empirically obtain the probability of a Type I error and the power for the permutation t-test as compared to Student's t-test and the Mann-Whitney U-test. Empirical results showed differences for different sample sizes, variance ratios,…
Descriptors: Nonparametric Statistics, Research Methodology, Statistical Analysis, Statistical Significance
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Feir-Walsh, Betty J.; Toothaker, Larry E. – Educational and Psychological Measurement, 1974
Descriptors: Analysis of Variance, Comparative Analysis, Hypothesis Testing, Nonparametric Statistics
Keats, John B.; Brewer, James K. – 1971
This paper presents an index of goodness-of-fit for comparing m models over n trials. The index allows for differentiated weighting of the trials as to their importance in the comparison of the models. Several possible weighting schemes are suggested and the conditions on the weights which assure asymptotic normality of the index distribution are…
Descriptors: Goodness of Fit, Hypothesis Testing, Mathematical Models, Nonparametric Statistics
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Edgington, Eugene S.; Haller, Otto – Educational and Psychological Measurement, 1984
This paper explains how to combine probabilities from discrete distributions, such as probability distributions for nonparametric tests. (Author/BW)
Descriptors: Computer Software, Data Analysis, Hypothesis Testing, Mathematical Formulas
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Olejnik, Stephen F.; Algina, James – Evaluation Review, 1985
Five distribution-free alternatives to parametric analysis of covariance are presented and demonstrated: Quade's distribution-free test, Puri and Sen's solution, McSweeney and Porter's rank transformation, Burnett and Barr's rank difference scores, and Shirley's general linear model solution. The results of simulation studies regarding Type I…
Descriptors: Analysis of Covariance, Comparative Analysis, Hypothesis Testing, Monte Carlo Methods
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Roberge, James J. – Educational and Psychological Measurement, 1971
Descriptors: Comparative Analysis, Computer Programs, Hypothesis Testing, Nonparametric Statistics