NotesFAQContact Us
Collection
Advanced
Search Tips
Laws, Policies, & Programs
What Works Clearinghouse Rating
Showing 1 to 15 of 55 results Save | Export
Peer reviewed Peer reviewed
Direct linkDirect link
Johnson, Roger W. – Journal of Statistics and Data Science Education, 2022
For ease of instruction in the classroom, the one-way analysis of variance F statistic is rewritten in terms of pairwise differences in individual sample means instead of differences of individual sample means from the overall sample mean. Likewise, the Kruskal-Wallis statistic may be rewritten in terms of pairwise differences in individual…
Descriptors: Statistics Education, Statistical Analysis, Hypothesis Testing, Sampling
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
Peer reviewed Peer reviewed
Direct linkDirect link
Kelcey, Ben; Spybrook, Jessaca; Dong, Nianbo; Bai, Fangxing – Journal of Research on Educational Effectiveness, 2020
Professional development for teachers is regarded as one of the principal pathways through which we can understand and cultivate effective teaching and improve student outcomes. A critical component of studies that seek to improve teaching through professional development is the detailed assessment of the intermediate teacher development processes…
Descriptors: Faculty Development, Educational Research, Randomized Controlled Trials, Research Design
Peer reviewed Peer reviewed
PDF on ERIC Download full text
Nordstokke, David W.; Colp, S. Mitchell – Practical Assessment, Research & Evaluation, 2018
Often, when testing for shift in location, researchers will utilize nonparametric statistical tests in place of their parametric counterparts when there is evidence or belief that the assumptions of the parametric test are not met (i.e., normally distributed dependent variables). An underlying and often unattended to assumption of nonparametric…
Descriptors: Nonparametric Statistics, Statistical Analysis, Monte Carlo Methods, Sample Size
Ayodele, Alicia Nicole – ProQuest LLC, 2017
Within polytomous items, differential item functioning (DIF) can take on various forms due to the number of response categories. The lack of invariance at this level is referred to as differential step functioning (DSF). The most common DSF methods in the literature are the adjacent category log odds ratio (AC-LOR) estimator and cumulative…
Descriptors: Statistical Analysis, Test Bias, Test Items, Scores
Peer reviewed Peer reviewed
Direct linkDirect link
Pustejovsky, James Eric; Furman, Gleb – AERA Online Paper Repository, 2017
In linear regression models estimated by ordinary least squares, it is often desirable to use hypothesis tests and confidence intervals that remain valid in the presence of heteroskedastic errors. Wald tests based on heteroskedasticity-consistent covariance matrix estimators (HCCMEs, also known as sandwich estimators or simply "robust"…
Descriptors: Hypothesis Testing, Sample Size, Regression (Statistics), Computation
Peer reviewed Peer reviewed
Direct linkDirect link
Porter, Kristin E. – Journal of Research on Educational Effectiveness, 2018
Researchers are often interested in testing the effectiveness of an intervention on multiple outcomes, for multiple subgroups, at multiple points in time, or across multiple treatment groups. The resulting multiplicity of statistical hypothesis tests can lead to spurious findings of effects. Multiple testing procedures (MTPs) are statistical…
Descriptors: Statistical Analysis, Program Effectiveness, Intervention, Hypothesis Testing
Peer reviewed Peer reviewed
PDF on ERIC Download full text
McGrath, April – Teaching & Learning Inquiry, 2016
Quantitative results from empirical studies are common in the field of Scholarship of Teaching and Learning (SoTL), but it is important to remain aware of what the results from our studies can, and cannot, tell us. Oftentimes studies conducted to examine teaching and learning are constrained by class size. Small sample sizes negatively influence…
Descriptors: Scholarship, Instruction, Learning, Class Size
Porter, Kristin E. – Grantee Submission, 2017
Researchers are often interested in testing the effectiveness of an intervention on multiple outcomes, for multiple subgroups, at multiple points in time, or across multiple treatment groups. The resulting multiplicity of statistical hypothesis tests can lead to spurious findings of effects. Multiple testing procedures (MTPs) are statistical…
Descriptors: Statistical Analysis, Program Effectiveness, Intervention, Hypothesis Testing
Porter, Kristin E. – MDRC, 2016
In education research and in many other fields, researchers are often interested in testing the effectiveness of an intervention on multiple outcomes, for multiple subgroups, at multiple points in time, or across multiple treatment groups. The resulting multiplicity of statistical hypothesis tests can lead to spurious findings of effects. Multiple…
Descriptors: Statistical Analysis, Program Effectiveness, Intervention, Hypothesis Testing
Peer reviewed Peer reviewed
Direct linkDirect link
Weller, Susan C. – Field Methods, 2015
This article presents a simple approach to making quick sample size estimates for basic hypothesis tests. Although there are many sources available for estimating sample sizes, methods are not often integrated across statistical tests, levels of measurement of variables, or effect sizes. A few parameters are required to estimate sample sizes and…
Descriptors: Sample Size, Statistical Analysis, Computation, Hypothesis Testing
Peer reviewed Peer reviewed
PDF on ERIC Download full text
Ryan, Wendy L.; St. Iago-McRae, Ezry – Bioscene: Journal of College Biology Teaching, 2016
Experimentation is the foundation of science and an important process for students to understand and experience. However, it can be difficult to teach some aspects of experimentation within the time and resource constraints of an academic semester. Interactive models can be a useful tool in bridging this gap. This freely accessible simulation…
Descriptors: Research Design, Simulation, Animals, Animal Behavior
Chilca Alva, Manuel L. – Journal of Educational Psychology - Propositos y Representaciones, 2017
This study was intended to establish whether self-esteem and study habits correlate with academic performance among university students. Research conducted was descriptive observational, multivariate or cross-sectional factorial in nature. The study population consisted of 196 students enrolled in a Basic Mathematics 1 class at the School of…
Descriptors: Foreign Countries, Self Esteem, Study Habits, Academic Achievement
Peer reviewed Peer reviewed
PDF on ERIC Download full text
de Winter, J. C .F. – Practical Assessment, Research & Evaluation, 2013
Researchers occasionally have to work with an extremely small sample size, defined herein as "N" less than or equal to 5. Some methodologists have cautioned against using the "t"-test when the sample size is extremely small, whereas others have suggested that using the "t"-test is feasible in such a case. The present…
Descriptors: Sample Size, Statistical Analysis, Hypothesis Testing, Simulation
Peer reviewed Peer reviewed
Direct linkDirect link
Barr, Dale J.; Levy, Roger; Scheepers, Christoph; Tily, Harry J. – Journal of Memory and Language, 2013
Linear mixed-effects models (LMEMs) have become increasingly prominent in psycholinguistics and related areas. However, many researchers do not seem to appreciate how random effects structures affect the generalizability of an analysis. Here, we argue that researchers using LMEMs for confirmatory hypothesis testing should minimally adhere to the…
Descriptors: Hypothesis Testing, Psycholinguistics, Models, Monte Carlo Methods
Previous Page | Next Page ยป
Pages: 1  |  2  |  3  |  4