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John Mart V. DelosReyes; Miguel A. Padilla – Journal of Experimental Education, 2024
Estimating confidence intervals (CIs) for the correlation has been a challenge because the correlation sampling distribution changes depending on the correlation magnitude. The Fisher z-transformation was one of the first attempts at estimating correlation CIs but has historically shown to not have acceptable coverage probability if data were…
Descriptors: Research Problems, Correlation, Intervals, Computation
Kulinskaya, Elena; Hoaglin, David C. – Research Synthesis Methods, 2023
For estimation of heterogeneity variance T[superscript 2] in meta-analysis of log-odds-ratio, we derive new mean- and median-unbiased point estimators and new interval estimators based on a generalized Q statistic, Q[subscript F], in which the weights depend on only the studies' effective sample sizes. We compare them with familiar estimators…
Descriptors: Q Methodology, Statistical Analysis, Meta Analysis, Intervals
Shieh, Gwowen – Journal of Experimental Education, 2019
The analysis of covariance (ANCOVA) is a useful statistical procedure that incorporates covariate features into the adjustment of treatment effects. The consequences of omitted prognostic covariates on the statistical inferences of ANCOVA are well documented in the literature. However, the corresponding influence on sample-size calculations for…
Descriptors: Sample Size, Statistical Analysis, Computation, Accuracy
Inzunsa Cazares, Santiago – North American Chapter of the International Group for the Psychology of Mathematics Education, 2016
This article presents the results of a qualitative research with a group of 15 university students of social sciences on informal inferential reasoning developed in a computer environment on concepts involved in the confidence intervals. The results indicate that students developed a correct reasoning about sampling variability and visualized…
Descriptors: Qualitative Research, College Students, Inferences, Logical Thinking
Shieh, Gwowen – Journal of Experimental Education, 2015
Analysis of variance is one of the most frequently used statistical analyses in the behavioral, educational, and social sciences, and special attention has been paid to the selection and use of an appropriate effect size measure of association in analysis of variance. This article presents the sample size procedures for precise interval estimation…
Descriptors: Statistical Analysis, Sample Size, Computation, Effect Size
Murray, Arthur; Hart, Ian – Physics Education, 2012
The "radioactive dice" experiment is a commonly used classroom analogue to model the decay of radioactive nuclei. However, the value of the half-life obtained from this experiment differs significantly from that calculated for real nuclei decaying exponentially with the same decay constant. This article attempts to explain the discrepancy and…
Descriptors: Science Experiments, Intervals, Experiments, Prediction
Noll, Jennifer; Shaughnessy, J. Michael – Journal for Research in Mathematics Education, 2012
Sampling tasks and sampling distributions provide a fertile realm for investigating students' conceptions of variability. A project-designed teaching episode on samples and sampling distributions was team-taught in 6 research classrooms (2 middle school and 4 high school) by the investigators and regular classroom mathematics teachers. Data…
Descriptors: Sampling, Mathematics Teachers, Middle Schools, High Schools
Dunst, Carl J.; Hamby, Deborah W. – Journal of Intellectual & Developmental Disability, 2012
This paper includes a nontechnical description of methods for calculating effect sizes in intellectual and developmental disability studies. Different hypothetical studies are used to illustrate how null hypothesis significance testing (NHST) and effect size findings can result in quite different outcomes and therefore conflicting results. Whereas…
Descriptors: Intervals, Developmental Disabilities, Statistical Significance, Effect Size
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
Algina, James; Keselman, Harvey J.; Penfield, Randall J. – Educational and Psychological Measurement, 2008
A squared semipartial correlation coefficient ([Delta]R[superscript 2]) is the increase in the squared multiple correlation coefficient that occurs when a predictor is added to a multiple regression model. Prior research has shown that coverage probability for a confidence interval constructed by using a modified percentile bootstrap method with…
Descriptors: Intervals, Correlation, Probability, Multiple Regression Analysis
Kazi, Mansoor A. F.; Pagkos, Brian; Milch, Heidi A. – Research on Social Work Practice, 2011
Objectives: The purpose of this study was to develop a realist evaluation paradigm in social work evidence-based practice. Method: Wraparound (at Gateway-Longview Inc., New York) used a reliable outcome measure and an electronic database to systematically collect and analyze data on the interventions, the client demographics and circumstances, and…
Descriptors: Intervals, Data Analysis, Social Work, Sample Size
Navarrete-Alvarez, Esteban; Rosales-Moreno, Maria Jesus; Huete-Morales, Maria Dolores – Online Submission, 2010
Statistics teaching should not be carried out in the same way for all kinds of university students. Instead, teaching statistics should take into account the different fields of study that students have chosen. For example, students of sciences or engineering have different interests and backgrounds compared to students of any social or juridical…
Descriptors: Academic Achievement, Statistics, Labor, Teaching Methods
Algina, James; Keselman, H. J.; Penfield, Randall D. – Educational and Psychological Measurement, 2007
The increase in the squared multiple correlation coefficient ([Delta]R[squared]) associated with a variable in a regression equation is a commonly used measure of importance in regression analysis. The coverage probability that an asymptotic and percentile bootstrap confidence interval includes [Delta][rho][squared] was investigated. As expected,…
Descriptors: Probability, Intervals, Multiple Regression Analysis, Correlation
Cheung, Mike W. L. – Structural Equation Modeling: A Multidisciplinary Journal, 2007
Mediators are variables that explain the association between an independent variable and a dependent variable. Structural equation modeling (SEM) is widely used to test models with mediating effects. This article illustrates how to construct confidence intervals (CIs) of the mediating effects for a variety of models in SEM. Specifically, mediating…
Descriptors: Structural Equation Models, Probability, Intervals, Sample Size
Algina, James; Olejnik, Stephen – Multivariate Behavioral Research, 2003
Tables for selecting sample size in correlation studies are presented. Some of the tables allow selection of sample size so that r (or r[squared], depending on the statistic the researcher plans to interpret) will be within a target interval around the population parameter with probability 0.95. The intervals are [plus or minus] 0.05, [plus or…
Descriptors: Probability, Intervals, Sample Size, Multiple Regression Analysis
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