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Conant, Darcy Lynn – ProQuest LLC, 2013
Stochastic understanding of probability distribution undergirds development of conceptual connections between probability and statistics and supports development of a principled understanding of statistical inference. This study investigated the impact of an instructional course intervention designed to support development of stochastic…
Descriptors: Statistics, Probability, Statistical Distributions, Statistical Inference
What Works Clearinghouse, 2014
This "What Works Clearinghouse Procedures and Standards Handbook (Version 3.0)" provides a detailed description of the standards and procedures of the What Works Clearinghouse (WWC). The remaining chapters of this Handbook are organized to take the reader through the basic steps that the WWC uses to develop a review protocol, identify…
Descriptors: Educational Research, Guides, Intervention, Classification
Sun, Shuyan; Pan, Wei; Wang, Lihshing Leigh – Journal of Educational Psychology, 2010
Null hypothesis significance testing has dominated quantitative research in education and psychology. However, the statistical significance of a test as indicated by a p-value does not speak to the practical significance of the study. Thus, reporting effect size to supplement p-value is highly recommended by scholars, journal editors, and academic…
Descriptors: Effect Size, Statistical Inference, Statistical Significance, Data Interpretation
Maraun, Michael; Gabriel, Stephanie – Psychological Methods, 2010
In his article, "An Alternative to Null-Hypothesis Significance Tests," Killeen (2005) urged the discipline to abandon the practice of "p[subscript obs]"-based null hypothesis testing and to quantify the signal-to-noise characteristics of experimental outcomes with replication probabilities. He described the coefficient that he…
Descriptors: Hypothesis Testing, Statistical Inference, Probability, Statistical Significance
LeMire, Steven D. – Journal of Statistics Education, 2010
This paper proposes an argument framework for the teaching of null hypothesis statistical testing and its application in support of research. Elements of the Toulmin (1958) model of argument are used to illustrate the use of p values and Type I and Type II error rates in support of claims about statistical parameters and subject matter research…
Descriptors: Hypothesis Testing, Relationship, Statistical Significance, Models
Kim, Se-Kang – International Journal of Testing, 2010
The aim of the current study is to validate the invariance of major profile patterns derived from multidimensional scaling (MDS) by bootstrapping. Profile Analysis via Multidimensional Scaling (PAMS) was employed to obtain profiles and bootstrapping was used to construct the sampling distributions of the profile coordinates and the empirical…
Descriptors: Intervals, Multidimensional Scaling, Profiles, Evaluation
Tonidandel, Scott; LeBreton, James M.; Johnson, Jeff W. – Psychological Methods, 2009
Relative weight analysis is a procedure for estimating the relative importance of correlated predictors in a regression equation. Because the sampling distribution of relative weights is unknown, researchers using relative weight analysis are unable to make judgments regarding the statistical significance of the relative weights. J. W. Johnson…
Descriptors: Multiple Regression Analysis, Statistical Significance, Statistical Inference, Bias
Hudson, Peter; Matthews, Kelly – Journal of Science and Mathematics Education in Southeast Asia, 2012
Women are underrepresented in science, technology, engineering and mathematics (STEM) areas in university settings; however this may be the result of attitude rather than aptitude. There is widespread agreement that quantitative problem-solving is essential for graduate competence and preparedness in science and other STEM subjects. The research…
Descriptors: Females, Student Attitudes, Statistical Significance, Males
Kadhi, T.; Palasota, A.; Holley, D.; Rudley, D. – Online Submission, 2010
The following report gives the statistical findings of the 2009-2010 Watson-Glaser test. Data is pre-existing and was given to the Evaluator by email from the Director, Center for Legal Pedagogy. Statistical analyses were run using SPSS 17 to address the following questions: 1. What are the statistical descriptors of the Watson-Glaser results of…
Descriptors: Pretests Posttests, Statistical Significance, Classification, Achievement Tests
Dorman, Jeffrey P. – International Journal of Research & Method in Education, 2008
This article discusses issues associated with statistical testing conducted with data from clustered school samples. Empirical researchers often conduct tests of statistical inference on sample data to ascertain the extent to which differences exist within groups in the population. Typically, much school-related data are collected from students.…
Descriptors: Testing, Statistical Significance, Statistical Inference, Data Analysis
Wang, Jianjun – International Journal of Research & Method in Education, 2008
As an alternative to statistical testing, effect size has a non-monotonic linkage with practical importance. Besides random variance and systematic bias, a proper interpretation of effect size hinges on its implication to outcomes of deductive and/or inductive enquiries. Consequently, a small effect size might suggest an important finding, and the…
Descriptors: Effect Size, Statistical Significance, Statistical Inference, Evaluation
A Critical Assessment of Null Hypothesis Significance Testing in Quantitative Communication Research
Levine, Timothy R.; Weber, Rene; Hullett, Craig; Park, Hee Sun; Lindsey, Lisa L. Massi – Human Communication Research, 2008
Null hypothesis significance testing (NHST) is the most widely accepted and frequently used approach to statistical inference in quantitative communication research. NHST, however, is highly controversial, and several serious problems with the approach have been identified. This paper reviews NHST and the controversy surrounding it. Commonly…
Descriptors: Communication Research, Testing, Statistical Significance, Statistical Inference
Overall, John E.; Tonidandel, Scott – Multivariate Behavioral Research, 2010
A previous Monte Carlo study examined the relative powers of several simple and more complex procedures for testing the significance of difference in mean rates of change in a controlled, longitudinal, treatment evaluation study. Results revealed that the relative powers depended on the correlation structure of the simulated repeated measurements.…
Descriptors: Monte Carlo Methods, Statistical Significance, Correlation, Depression (Psychology)
Eisenhauer, Joseph G. – Teaching Statistics: An International Journal for Teachers, 2009
Very little explanatory power is required in order for regressions to exhibit statistical significance. This article discusses some of the causes and implications. (Contains 2 tables.)
Descriptors: Statistical Significance, Educational Research, Sample Size, Probability
Levine, Timothy R.; Weber, Rene; Park, Hee Sun; Hullett, Craig R. – Human Communication Research, 2008
This paper offers a practical guide to use null hypotheses significance testing and its alternatives. The focus is on improving the quality of statistical inference in quantitative communication research. More consistent reporting of descriptive statistics, estimates of effect size, confidence intervals around effect sizes, and increasing the…
Descriptors: Intervals, Communication Research, Testing, Statistical Significance

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