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Moreno, R. – Journal of Computer Assisted Learning, 2006
Does the modality of instructional messages affect learning? How does it affect different media? In this paper, I offer an answer to these questions by first proposing a theoretical framework from which effective instructional methods can be derived. Then, I report a set of studies where one method, the modality principle, was tested across…
Descriptors: Teaching Methods, Learning Modalities, Instructional Effectiveness, Hypothesis Testing
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Patalano, Andrea L.; Chin-Parker, Seth; Ross, Brian H. – Journal of Memory and Language, 2006
Category-based inference is crucial for using past experiences to make sense of new ones. One challenge to inference of this kind is that most entities in the world belong to multiple categories (e.g., a jogger, a professor, and a vegetarian). We tested the hypothesis that the "degree of coherence" of a category-the degree to which category…
Descriptors: Rhetoric, Inferences, Social Influences, Classification
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Hollingworth, Andrew – Journal of Experimental Psychology: Learning, Memory, and Cognition, 2006
This study investigated whether and how visual representations of individual objects are bound in memory to scene context. Participants viewed a series of naturalistic scenes, and memory for the visual form of a target object in each scene was examined in a 2-alternative forced-choice test, with the distractor object either a different object…
Descriptors: Visual Learning, Memory, Visual Stimuli, Hypothesis Testing
Tam, Alice Yu-Wen; Wisenbaker, Joseph M. – 1996
The robustness with respect to Type I error and the power of a proposed test statistic in testing the conjoint hypotheses of mean and variability equality were examined in this simulation study. The conjoint test utilizes the maximum p-value from separate tests of equality of means and equality of variability as its p-value to control the Type I…
Descriptors: Analysis of Variance, Hypothesis Testing, Power (Statistics), Robustness (Statistics)
Chatham, Kathy – 1999
Contrasts or comparisons can be used to investigate specific differences between means. Contrasts, as explained by B. Thompson (1985, 1994) are coding vectors that mathematically express hypotheses. The most basic categories of contrasts are planned and unplanned. The purpose of this paper is to explain the relative advantages of using planned…
Descriptors: Coding, Comparative Analysis, Correlation, Hypothesis Testing
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Tritchler, D. L.; Pedrini, D. T. – Educational and Psychological Measurement, 1975
Considered in this paper are a mathematical discussion and an algorithm, and a computer program for Fisher's test. (Author)
Descriptors: Algorithms, Computer Programs, Hypothesis Testing, Input Output
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Overall, John E.; Woodward J. Arthur – Psychometrika, 1974
A procedure for testing heterogeneity of variance is developed which generalizes readily to complex, multi-factor experimental designs. Monte Carlo studies indicate that the Z-variance test statistic presented here yields results equivalent to other familiar tests for heterogeneity of variance in simple one-way designs where comparisons are…
Descriptors: Analysis of Variance, Hypothesis Testing, Research Design, Sampling
Sinclair, Hermina deZwart; O'Brien, Thomas C. – 1979
Piagetian research provides the focus of this article in which Professor Thomas C. O'Brien interviews Professor Hermina Sinclair. Aspects of children's thinking that prefigure scientific theory construction are described and the influence of schooling in inhibiting or suppressing a theory-building human tendency is briefly discussed. The…
Descriptors: Children, Cognitive Development, Generalization, Hypothesis Testing
Koffler, Stephen L. – 1982
Too often researchers rely upon the classical normal theory parametric tests to analyze non-normal data, even though the tests may not be robust to violations of that assumption. Fligner's class of two-sample tests for scale is an important development because the test is distribution-free and has desirable properties. This paper outlines the…
Descriptors: Hypothesis Testing, Nonparametric Statistics, Research Problems, Statistical Analysis
Bennett, Richard P. – 1983
The results of a study of find alternative techniques for testing distributional normality are presented. A group of statistical techniques--some established and some new--were compared using empirical techniques. One new technique which appears to have higher power than the Lilliefors test was subjected to a better definition. Distributions under…
Descriptors: Comparative Analysis, Hypothesis Testing, Power (Statistics), Sample Size
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Jackson, Douglas N.; Morf, Martin E. – Multivariate Behavioral Research, 1974
A method is proposed and illustrated for estimating the degree to which a factor rotation to a hypothesized target represents an improvement over rotation to a random target. (Author)
Descriptors: Factor Analysis, Goodness of Fit, Hypothesis Testing, Matrices
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Levine, Marvin – Journal of Experimental Child Psychology, 1974
Descriptors: Adults, Age Groups, Children, Hypothesis Testing
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Vitaliano, Peter P.; Halperin, Silas – Educational and Psychological Measurement, 1975
Descriptors: Computer Programs, Hypothesis Testing, Matrices, Sampling
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Lienert, G. A.; Krauth, J. – Educational and Psychological Measurement, 1975
Configural frequency analysis (CFA), a new method for identifying types, is illustrated numerically. Relations to latent class analysis and to factor analysis are discussed. It is suggested to use CFA as a type-defining method instead of factor analysis if the variables are linked not only by first but also by higher-order associations. (RC)
Descriptors: Classification, Factor Analysis, Hypothesis Testing, Mathematical Models
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Cooper, Martin – Educational and Psychological Measurement, 1975
A new test for increasing or decreasing trend in a set of observations is presented. Rather than making specific paired comparisons, as in the Cox and Stuart tests for trend, the user of the new test makes the comparisons of all possible pairs of observations. (Author)
Descriptors: Comparative Analysis, Hypothesis Testing, Nonparametric Statistics, Statistical Significance
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