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Lund, Thorleif – Scandinavian Journal of Educational Research, 2022
Criteria are briefly proposed for final conclusions, research problems, and research hypotheses in quantitative research. Moreover, based on a proposed definition of applied and basic/general research, it is argued that (1) in applied quantitative research, while research problems are necessary, research hypotheses are unjustified, and that (2) in…
Descriptors: Research Problems, Research Methodology, Hypothesis Testing, Statistical Analysis
Vembye, Mikkel Helding; Pustejovsky, James Eric; Pigott, Therese Deocampo – Journal of Educational and Behavioral Statistics, 2023
Meta-analytic models for dependent effect sizes have grown increasingly sophisticated over the last few decades, which has created challenges for a priori power calculations. We introduce power approximations for tests of average effect sizes based upon several common approaches for handling dependent effect sizes. In a Monte Carlo simulation, we…
Descriptors: Meta Analysis, Robustness (Statistics), Statistical Analysis, Models
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
Jane E. Miller – Numeracy, 2023
Students often believe that statistical significance is the only determinant of whether a quantitative result is "important." In this paper, I review traditional null hypothesis statistical testing to identify what questions inferential statistics can and cannot answer, including statistical significance, effect size and direction,…
Descriptors: Statistical Significance, Holistic Approach, Statistical Inference, Effect Size
Thompson, W. Burt – Teaching of Psychology, 2019
When a psychologist announces a new research finding, it is often based on a rejected null hypothesis. However, if that hypothesis is true, the claim is a false alarm. Many students mistakenly believe that the probability of committing a false alarm equals alpha, the criterion for statistical significance, which is typically set at 5%. Instructors…
Descriptors: Statistical Analysis, Hypothesis Testing, Misconceptions, Data Interpretation
Blaine, Bruce Evan – Scholarship and Practice of Undergraduate Research, 2019
Reproducibility crises have arisen in psychology and other behavioral sciences, spurring efforts to ensure research findings are credible and replicable. Although reforms are occurring at professional levels in terms of new publication parameters and open science initiatives, the credibility and reproducibility of undergraduate research deserves…
Descriptors: Undergraduate Students, Student Research, Behavioral Science Research, Research Methodology
Kang, Yoonjeong; Hancock, Gregory R. – Journal of Experimental Education, 2017
Structured means analysis is a very useful approach for testing hypotheses about population means on latent constructs. In such models, a z test is most commonly used for testing the statistical significance of the relevant parameter estimates or of the differences between parameter estimates, where a z value is computed based on the asymptotic…
Descriptors: Models, Statistical Analysis, Hypothesis Testing, Statistical Significance
Goodboy, Alan K. – Communication Education, 2017
For decades, instructional communication scholars have relied predominantly on cross-sectional survey methods to generate empirical associations between effective teaching and student learning. These studies typically correlate students' perceptions of their instructor's teaching behaviors with subjective self-report assessments of their own…
Descriptors: Educational Research, Communication Strategies, Teaching Methods, Learning Processes
Hicks, Tyler; Rodríguez-Campos, Liliana; Choi, Jeong Hoon – American Journal of Evaluation, 2018
To begin statistical analysis, Bayesians quantify their confidence in modeling hypotheses with priors. A prior describes the probability of a certain modeling hypothesis apart from the data. Bayesians should be able to defend their choice of prior to a skeptical audience. Collaboration between evaluators and stakeholders could make their choices…
Descriptors: Bayesian Statistics, Evaluation Methods, Statistical Analysis, Hypothesis Testing
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
McBee, Matthew T.; Makel, Matthew C.; Peters, Scott J.; Matthews, Michael S. – Gifted Child Quarterly, 2018
Current practices in study design and data analysis have led to low reproducibility and replicability of findings in fields such as psychology, medicine, biology, and economics. Because gifted education research relies on the same underlying statistical and sociological paradigms, it is likely that it too suffers from these problems. This article…
Descriptors: Academically Gifted, Research Methodology, Social Psychology, Research
Campitelli, Guillermo; Macbeth, Guillermo; Ospina, Raydonal; Marmolejo-Ramos, Fernando – Educational and Psychological Measurement, 2017
We present three strategies to replace the null hypothesis statistical significance testing approach in psychological research: (1) visual representation of cognitive processes and predictions, (2) visual representation of data distributions and choice of the appropriate distribution for analysis, and (3) model comparison. The three strategies…
Descriptors: Research Methodology, Hypothesis Testing, Psychology, Social Science Research
Pitan, Oluyomi S.; Adedeji, Segun O. – Africa Education Review, 2016
This study investigated demographic characteristics such as type of university attended, course of study and gender as determinants of duration of unemployment among university graduates in Nigeria. Data were collected from 1 451 employed university graduates in 300 firms in Nigeria. Results showed a significant difference between duration of…
Descriptors: Demography, Unemployment, College Graduates, Foreign Countries
Bainter, Sierra A.; Curran, Patrick J. – Journal of Cognition and Development, 2015
Amid recent progress in cognitive development research, high-quality data resources are accumulating, and data sharing and secondary data analysis are becoming increasingly valuable tools. Integrative data analysis (IDA) is an exciting analytical framework that can enhance secondary data analysis in powerful ways. IDA pools item-level data across…
Descriptors: Data Analysis, Integrated Activities, Inferences, Statistical Analysis
Jarosz, Andrew F.; Wiley, Jennifer – Journal of Problem Solving, 2014
The purpose of this paper is to provide an easy template for the inclusion of the Bayes factor in reporting experimental results, particularly as a recommendation for articles in the "Journal of Problem Solving." The Bayes factor provides information with a similar purpose to the "p"-value--to allow the researcher to make…
Descriptors: Problem Solving, Bayesian Statistics, Statistical Inference, Computation