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Munoz-Rubke, Felipe; Almuna, Felipe; Duemler, Jaclyn; Velásquez, Eloísa – International Journal of Science Education, Part B: Communication and Public Engagement, 2023
The COVID-19 pandemic revealed that many countries have failed to provide the general population with the cognitive tools to thoroughly understand and cope with a global health crisis. While scientists and leaders worldwide have struggled to discover ways to contain the spread of the virus, this difficult task has become overwhelming due to the…
Descriptors: COVID-19, Pandemics, Mathematics Instruction, Statistics Education
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Griffiths, Thomas L.; Chater, Nick; Norris, Dennis; Pouget, Alexandre – Psychological Bulletin, 2012
Bowers and Davis (2012) criticize Bayesian modelers for telling "just so" stories about cognition and neuroscience. Their criticisms are weakened by not giving an accurate characterization of the motivation behind Bayesian modeling or the ways in which Bayesian models are used and by not evaluating this theoretical framework against specific…
Descriptors: Bayesian Statistics, Psychology, Brain, Models
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Hahn, Ulrike; Warren, Paul A. – Psychological Review, 2010
We (Hahn & Warren, 2009) recently proposed a new account of the systematic errors and biases that appear to be present in people's perception of randomly generated events. In a comment on that article, Sun, Tweney, and Wang (2010) critiqued our treatment of the gambler's fallacy. We had argued that this fallacy was less gross an error than it…
Descriptors: Probability, Incidence, Prediction, Misconceptions
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Sun, Yanlong; Tweney, Ryan D.; Wang, Hongbin – Psychological Review, 2010
On the basis of the statistical concept of waiting time and on computer simulations of the "probabilities of nonoccurrence" (p. 457) for random sequences, Hahn and Warren (2009) proposed that given people's experience of a finite data stream from the environment, the gambler's fallacy is not as gross an error as it might seem. We deal with two…
Descriptors: Statistics, Statistical Analysis, Probability, Time Perspective
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Gorard, Stephen – International Journal of Research & Method in Education, 2009
The author previously published a paper discussing how to conduct an analysis based on a cluster sample. In that paper, the author outlined several widely adopted alternative approaches, and pointed out that such approaches are anyway not needed for population figures, and not possible for non-probability samples. Thus, the author queried the…
Descriptors: Probability, Misconceptions, Reader Response, Research Methodology
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Killeen, Peter R. – Psychological Methods, 2010
Lecoutre, Lecoutre, and Poitevineau (2010) have provided sophisticated grounding for "p[subscript rep]." Computing it precisely appears, fortunately, no more difficult than doing so approximately. Their analysis will help move predictive inference into the mainstream. Iverson, Wagenmakers, and Lee (2010) have also validated…
Descriptors: Replication (Evaluation), Measurement Techniques, Research Design, Research Methodology
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Farmer, Jim – Australian Senior Mathematics Journal, 2008
In this article, the author responds to the paper "Exploring pre-service teachers' understanding of statistical variation: Implications for teaching and research" by Sashi Sharma (see EJ779107). In that paper, Sharma described a study "designed to investigate pre-service teachers' acknowledgment of variation in sampling and…
Descriptors: Preservice Teacher Education, Preservice Teachers, Statistical Analysis, Probability
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Cumming, Geoff – Psychological Methods, 2010
This comment offers three descriptions of "p[subscript rep]" that start with a frequentist account of confidence intervals, draw on R. A. Fisher's fiducial argument, and do not make Bayesian assumptions. Links are described among "p[subscript rep]," "p" values, and the probability a confidence interval will capture…
Descriptors: Replication (Evaluation), Measurement Techniques, Research Methodology, Validity