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Griffiths, Thomas L.; Kalish, Michael L. – Cognitive Science, 2007
Languages are transmitted from person to person and generation to generation via a process of iterated learning: people learn a language from other people who once learned that language themselves. We analyze the consequences of iterated learning for learning algorithms based on the principles of Bayesian inference, assuming that learners compute…
Descriptors: Probability, Diachronic Linguistics, Statistical Inference, Language Universals
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Klockars, Alan J.; Hancock, Gregory – Journal of Educational and Behavioral Statistics, 1997
The use of finite intersection tests (FIT) to unify methods for simultaneous inference and to test orthogonal contrasts is discussed. Multiple comparison procedures that combine FIT with sequential hypothesis testing are illustrated, and a simulation strategy is presented to generate values needed for FIT methods. (SLD)
Descriptors: Comparative Analysis, Hypothesis Testing, Simulation, Statistical Inference
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Meulders, Michel; De Boeck, Paul; Van Mechelen, Iven; Gelman, Andrew; Maris, Eric – Journal of Educational and Behavioral Statistics, 2001
Presents a fully Bayesian analysis for the Probability Matrix Decomposition (PMD) model using the Gibbs sampler. Identifies the advantages of this approach and illustrates the approach by applying the PMD model to opinions of respondents from different countries concerning the possibility of contracting AIDS in a specific situation. (SLD)
Descriptors: Bayesian Statistics, Matrices, Probability, Psychometrics
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Kane, Michael – Measurement: Interdisciplinary Research and Perspectives, 2004
The commentaries include a wealth of insightful and interesting observations and suggestions, and I appreciate each author taking the time to comment on my efforts. In responding to their suggestions, I am inclined to develop a few general points raised in the commentaries a bit further.
Descriptors: Test Validity, Test Reliability, Methods, Statistical Inference
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Lee, Michael D.; Wagenmakers, Eric-Jan – Psychological Review, 2005
D. Trafimow presented an analysis of null hypothesis significance testing (NHST) using Bayes's theorem. Among other points, he concluded that NHST is logically invalid, but that logically valid Bayesian analyses are often not possible. The latter conclusion reflects a fundamental misunderstanding of the nature of Bayesian inference. This view…
Descriptors: Psychology, Statistical Inference, Statistical Significance, Bayesian Statistics
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Lee, Michael D.; Wagenmakers, Eric-Jan – Psychological Review, 2005
This paper comments on the response offered by Trafimow on Lee and Wagenmakers comments on Trafimow's original article. It seems our comment should have made it clear that the objective Bayesian approach we advocate views probabilities neither as relative frequencies nor as belief states, but as degrees of plausibility assigned to propositions in…
Descriptors: Researchers, Probability, Statistical Inference, Bayesian Statistics
Churchwell, Don Wesley – ProQuest LLC, 2009
This study examined the relationship between STAR Math gains and TCAP composite scores. The purpose of this study was to determine if there was a significant relationship between STAR Math pretest and posttest gains over the course of the 2005-2006 academic year through the use of the STAR Math software program and TCAP math composite scores at…
Descriptors: Student Needs, Mathematics Achievement, Pretests Posttests, Computer Software
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Huett, Jason Bond; Young, Jon; Huett, Kimberly Cleaves; Moller, Leslie; Bray, Marty – Quarterly Review of Distance Education, 2008
The purpose of this research was to manipulate the component of confidence found in Keller's ARCS Model to enhance the confidence and performance of undergraduate students enrolled in an online course at a Texas University. This experiment used SAM Office 2003 and WebCT for the delivery of the tactics, strategies, confidence-enhancing e-mails…
Descriptors: Control Groups, Undergraduate Students, Online Courses, Instructional Effectiveness
Mount, Brian – 1993
This paper, presented at a conference of college admissions counselors, attempts to provide a brief overview of descriptive and inferential statistics for college admissions officers, in the hopes that it will encourage these admissions personnel to question assumptions more critically. The paper begins by defining statistics, specifically…
Descriptors: Admissions Officers, Higher Education, Marketing, Recruitment
Min, Kyung-Seok; Frank, Kenneth A. – 2002
Various statistical methods have been available to deal with missing data problems, but the difficulty is that they are based on somewhat restrictive assumptions that missing patterns are known or can be modeled with auxiliary information. This paper treats the presence of missing cases from the viewpoint that generalization as a sample does not…
Descriptors: Data Collection, Regression (Statistics), Research Methodology, Statistical Inference
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Barchard, Kimberly A.; Hakstian, A. Ralph – Educational and Psychological Measurement, 1997
The distinction between Type 1 and Type 12 sampling in connection with measurement data is discussed, and a method is presented for simulating data arising from Type 12 sampling. A Monte Carlo study is described that shows conditions under which precise confidence level control under Type 12 sampling is maintained. (SLD)
Descriptors: Models, Monte Carlo Methods, Sampling, Simulation
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Shipley, Bill – Structural Equation Modeling, 2003
Shows how to extend the inferential test of B. Shipley (2000), which is applicable to recursive path models without correlated errors, to a class of recursive path models that includes correlated errors. Discusses when the extended model is and is not superior to classical structural equation modeling. (SLD)
Descriptors: Correlation, Path Analysis, Statistical Inference, Structural Equation Models
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Timm, Neil H. – Multivariate Behavioral Research, 1995
The finite intersection test (FIT) developed by P. K. Krishnaiah (1964, 1965) is discussed and compared with more familiar methods for simultaneous inference. How the FIT can be used to analyze differences among all means for both univariate and multivariate experimental designs is explained. (SLD)
Descriptors: Comparative Analysis, Equations (Mathematics), Multivariate Analysis, Statistical Inference
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Helman, Danny – Teaching Statistics: An International Journal for Teachers, 2004
The national lottery is often portrayed as a game of pure chance with no room for strategy. This misperception seems to stem from the application of probability instead of expectancy considerations, and can be utilized to introduce the statistical concept of expectation.
Descriptors: Probability, Expectation, Statistics, Statistical Inference
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Konold, Cliff; Harradine, Anthony; Kazak, Sibel – International Journal of Computers for Mathematical Learning, 2007
In current curriculum materials for middle school students in the US, data and chance are considered as separate topics. They are then ideally brought together in the minds of high school or university students when they learn about statistical inference. In recent studies we have been attempting to build connections between data and chance in the…
Descriptors: Middle School Students, Computer Software, Statistical Inference, Statistical Distributions
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