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Rosenthal, Jeffrey S. – Teaching Statistics: An International Journal for Teachers, 2018
This article advocates that introductory statistics be taught by basing all calculations on a single simple margin-of-error formula and deriving all of the standard introductory statistical concepts (confidence intervals, significance tests, comparisons of means and proportions, etc) from that one formula. It is argued that this approach will…
Descriptors: Statistics, Introductory Courses, Computation, Statistical Analysis
Rutherford, Marion; Burns, Morag; Gray, Duncan; Bremner, Lynne; Clegg, Sarah; Russell, Lucy; Smith, Charlie; O'Hare, Anne – Journal of Autism and Developmental Disorders, 2018
The 'autism diagnosis crisis' and long waiting times for assessment are as yet unresolved, leading to undue stress and limiting access to effective support. There is therefore a significant need for evidence to support practitioners in the development of efficient services, delivering acceptable waiting times and effectively meeting guideline…
Descriptors: Autism, Pervasive Developmental Disorders, Clinical Diagnosis, Efficiency
Vaughan, Timothy S. – Journal of Statistics Education, 2015
This paper introduces a dataset and associated analysis of the scores of National Football League (NFL) games over the 2012, 2013, and first five weeks of the 2014 season. In the face of current media attention to "lopsided" scores in Thursday night games in the early part of the 2014 season, t-test results indicate no statistically…
Descriptors: Team Sports, Success, Scores, Statistics
Liu, Xiaofeng Steven – International Journal of Mathematical Education in Science and Technology, 2012
The statistical power of a significance test is closely related to the length of the confidence interval (i.e. estimate precision). In the case of a "Z" test, the length of the confidence interval can be expressed as a function of the statistical power. (Contains 1 figure and 1 table.)
Descriptors: Statistical Analysis, Intervals, Statistical Significance, Statistics
Taub, Gordon E.; McGrew, Kevin S.; Keith, Timothy Z. – Journal of Research in Childhood Education, 2015
This article examines the effect of improvements in timing/rhythmicity on mathematics achievement. A total of 86 participants attending 1st through 4th grades completed pre- and posttest measures of mathematics achievement from the Woodcock-Johnson III Tests of Achievement. Students in the experimental group participated in a 4-week intervention…
Descriptors: Elementary School Students, Elementary School Mathematics, Mathematics Achievement, Intervals
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
Rusticus, Shayna A.; Lovato, Chris Y. – Practical Assessment, Research & Evaluation, 2011
Assessing the comparability of different groups is an issue facing many researchers and evaluators in a variety of settings. Commonly, null hypothesis significance testing (NHST) is incorrectly used to demonstrate comparability when a non-significant result is found. This is problematic because a failure to find a difference between groups is not…
Descriptors: Medical Education, Evaluators, Intervals, Testing
Kehle, Thomas J.; Bray, Melissa A.; Chafouleas, Sandra M.; Kawano, Takuji – Psychology in the Schools, 2007
Criticism has been leveled against the use of statistical significance testing (SST) in many disciplines. However, the field of school psychology has been largely devoid of critiques of SST. Inspection of the primary journals in school psychology indicated numerous examples of SST with nonrandom samples and/or samples of convenience. In this…
Descriptors: Intervals, School Psychology, Effect Size, Statistical Significance
Thompson, Bruce – Psychology in the Schools, 2007
The present article provides a primer on (a) effect sizes, (b) confidence intervals, and (c) confidence intervals for effect sizes. Additionally, various admonitions for reformed statistical practice are presented. For example, a very important implication of the realization that there are dozens of effect size statistics is that "authors must…
Descriptors: Intervals, Effect Size, Statistical Analysis, Statistical Significance
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
Strang, Kenneth David – Practical Assessment, Research & Evaluation, 2009
This paper discusses how a seldom-used statistical procedure, recursive regression (RR), can numerically and graphically illustrate data-driven nonlinear relationships and interaction of variables. This routine falls into the family of exploratory techniques, yet a few interesting features make it a valuable compliment to factor analysis and…
Descriptors: Multicultural Education, Computer Software, Multiple Regression Analysis, Multidimensional Scaling
Statistical Significance, Effect Size Reporting, and Confidence Intervals: Best Reporting Strategies
Capraro, Robert M. – Journal for Research in Mathematics Education, 2004
With great interest the author read the May 2002 editorial in the "Journal for Research in Mathematics Education (JRME)" (King, 2002) regarding changes to the 5th edition of the "Publication Manual of the American Psychological Association" (APA, 2001). Of special note to him, and of great import to the field of mathematics education research, are…
Descriptors: Intervals, Mathematics Education, Effect Size, Educational Research
Mallinckrodt, Brent; Abraham, W. Todd; Wei, Meifen; Russell, Daniel W. – Journal of Counseling Psychology, 2006
P. A. Frazier, A. P. Tix, and K. E. Barron (2004) highlighted a normal theory method popularized by R. M. Baron and D. A. Kenny (1986) for testing the statistical significance of indirect effects (i.e., mediator variables) in multiple regression contexts. However, simulation studies suggest that this method lacks statistical power relative to some…
Descriptors: Statistical Significance, Multiple Regression Analysis, Simulation, Evaluation Methods
Hadley, Pamela A.; Holt, Janet K. – Journal of Speech, Language, and Hearing Research, 2006
The purpose of this study was to explore individual differences in children's tense onset growth trajectories and to determine whether any within- or between-child predictors could account for these differences. Twenty-two children with expressive vocabulary abilities in the low-average to below-average range participated. Sixteen children were at…
Descriptors: Models, Morphemes, Intervals, Vocabulary Development
Byrd, Jimmy K. – Educational Administration Quarterly, 2007
Purpose: The purpose of this study was to review research published by Educational Administration Quarterly (EAQ) during the past 10 years to determine if confidence intervals and effect sizes were being reported as recommended by the American Psychological Association (APA) Publication Manual. Research Design: The author examined 49 volumes of…
Descriptors: Research Design, Intervals, Statistical Inference, Effect Size

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