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Ernesto Sánchez; Victor Nozair García-Ríos; Francisco Sepúlveda – Educational Studies in Mathematics, 2024
Sampling distributions are fundamental for statistical inference, yet their abstract nature poses challenges for students. This research investigates the development of high school students' conceptions of sampling distribution through informal significance tests with the aid of digital technology. The study focuses on how technological tools…
Descriptors: High School Students, Concept Formation, Thinking Skills, Skill Development
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Sánchez Sánchez, Ernesto; García Rios, Víctor N.; Silvestre Castro, Eleazar; Licea, Guadalupe Carrasco – North American Chapter of the International Group for the Psychology of Mathematics Education, 2020
In this paper, we address the following questions: What misconceptions do high school students exhibit in their first encounter with significance test problems through a repeated sampling approach? Which theory or framework could explain the presence and features of such patterns? With brief prior instruction on the use of Fathom software to…
Descriptors: High School Students, Misconceptions, Statistical Significance, Testing
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Dogan, C. Deha – Eurasian Journal of Educational Research, 2017
Background: Most of the studies in academic journals use p values to represent statistical significance. However, this is not a good indicator of practical significance. Although confidence intervals provide information about the precision of point estimation, they are, unfortunately, rarely used. The infrequent use of confidence intervals might…
Descriptors: Sampling, Statistical Inference, Periodicals, Intervals
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Neale, Dave – Oxford Review of Education, 2015
Recently, Stephen Gorard has outlined strong objections to the use of significance testing in social research. He has argued, first, that as the samples used in social research are almost always non-random it is not possible to use inferential statistical techniques and, second, that even if a truly random sample were achieved, the logic behind…
Descriptors: Statistical Significance, Statistical Analysis, Sampling, Probability
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García, Víctor N.; Sánchez, Ernesto – North American Chapter of the International Group for the Psychology of Mathematics Education, 2017
In the present study we analyze how students reason about or make inferences given a particular hypothesis testing problem (without having studied formal methods of statistical inference) when using Fathom. They use Fathom to create an empirical sampling distribution through computer simulation. It is found that most student´s reasoning rely on…
Descriptors: High School Students, Logical Thinking, Hypothesis Testing, Computer Simulation
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Leth-Steensen, Craig; Gallitto, Elena – Educational and Psychological Measurement, 2016
A large number of approaches have been proposed for estimating and testing the significance of indirect effects in mediation models. In this study, four sets of Monte Carlo simulations involving full latent variable structural equation models were run in order to contrast the effectiveness of the currently popular bias-corrected bootstrapping…
Descriptors: Mediation Theory, Structural Equation Models, Monte Carlo Methods, Simulation
Woodruff, David; Wu, Yi-Fang – ACT, Inc., 2012
The purpose of this paper is to illustrate alpha's robustness and usefulness, using actual and simulated educational test data. The sampling properties of alpha are compared with the sampling properties of several other reliability coefficients: Guttman's lambda[subscript 2], lambda[subscript 4], and lambda[subscript 6]; test-retest reliability;…
Descriptors: Sampling, Test Reliability, Item Response Theory, Statistical Inference
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Ruscio, John; Gera, Benjamin Lee – Multivariate Behavioral Research, 2013
Researchers are strongly encouraged to accompany the results of statistical tests with appropriate estimates of effect size. For 2-group comparisons, a probability-based effect size estimator ("A") has many appealing properties (e.g., it is easy to understand, robust to violations of parametric assumptions, insensitive to outliers). We review…
Descriptors: Psychological Studies, Gender Differences, Researchers, Test Results
Spinella, Sarah – Online Submission, 2011
As result replicability is essential to science and difficult to achieve through external replicability, the present paper notes the insufficiency of null hypothesis statistical significance testing (NHSST) and explains the bootstrap as a plausible alternative, with a heuristic example to illustrate the bootstrap method. The bootstrap relies on…
Descriptors: Sampling, Statistical Inference, Statistical Significance, Error of Measurement
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Buchanan, Taylor L.; Lohse, Keith R. – Measurement in Physical Education and Exercise Science, 2016
We surveyed researchers in the health and exercise sciences to explore different areas and magnitudes of bias in researchers' decision making. Participants were presented with scenarios (testing a central hypothesis with p = 0.06 or p = 0.04) in a random order and surveyed about what they would do in each scenario. Participants showed significant…
Descriptors: Researchers, Attitudes, Statistical Significance, Bias
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Rueger, Sandra Yu; Jenkins, Lyndsay N. – School Psychology Quarterly, 2014
The purpose of the current study is to investigate the effects of frequency of peer victimization experiences on psychological and academic adjustment during early adolescence, with a focus on testing psychological adjustment as a mediator, as well as differences based on gender and type of victimization. The sample in this short-term longitudinal…
Descriptors: Bullying, Peer Relationship, Victims, Incidence
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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
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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
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Vacha-Haase, Tammi; Thompson, Bruce – Measurement and Evaluation in Counseling and Development, 1998
Responds to Biskin's comments (this issue) on the significance test controversy. Highlights areas of agreement (importance of replication evidence, importance of effect sizes) and disagreement (influence of sample size, evaluation of populations vs. samples, significance of Carver's article). Includes further recommendations for reporting research…
Descriptors: Data Interpretation, Hypothesis Testing, Psychological Studies, Sampling
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Kirk, Roger E. – Educational and Psychological Measurement, 2001
Makes the case that science is best served when researchers focus on the size of effects and their practical significance. Advocates the use of confidence intervals for deciding whether chance or sampling variability is an unlikely explanation for an observed effect. Calls for more emphasis on effect sizes in the next edition of the American…
Descriptors: Effect Size, Hypothesis Testing, Psychology, Research Reports
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