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Three Strategies for the Critical Use of Statistical Methods in Psychological Research
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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
Probability Distributions of Minkowski Distances between Discrete Random Variables.
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Schroger, Erich; And Others – Educational and Psychological Measurement, 1993
Minkowski distances are used to indicate similarity of two vectors in an N-dimensional space. How to compute the probability function, the expectation, and the variance for Minkowski distances and the special cases City-block distance and Euclidean distance. Critical values for tests of significance are presented in tables. (SLD)
Descriptors: Equations (Mathematics), Probability, Statistical Distributions, Statistical Significance
Difference Tests for Distributions of Ratings.
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Aiken, Lewis R.; Aiken, Timothy A. – Educational and Psychological Measurement, 1986
Three exact probability tests, counterparts of t tests for single sample, independent samples, and dependent samples, are described for data obtained from ratings on "m" scales by a single rater or on a single scale by "n" raters. (LMO)
Descriptors: Nonparametric Statistics, Probability, Rating Scales, Statistical Distributions
Approximating Probability Levels for Testing Null Hypotheses with Noncentral F Distributions.
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Fowler, Robert L. – Educational and Psychological Measurement, 1984
This study compared two approximations for normalizing noncentral F distributions: one based on the square root of the chi-square distribution (SRA), the other derived from a cube root of the chi-square distribution (CRA). The CRA was superior, and generally provided an excellent approximation for noncentral F. (Author/BW)
Descriptors: Estimation (Mathematics), Hypothesis Testing, Mathematical Formulas, Probability
Robust Tests for the Equality of Two Correlation Coefficients: A Monte Carlo Study.
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Yu, Mimi C.; Dunn, Olive Jean – Educational and Psychological Measurement, 1982
Eight asymptotically robust tests of population correlation coefficient equality are proposed and are studied along with two parametric tests. Monte Carlo simulation is used to compare the small sample performance of these ten procedures. The sampled distributions consist of the normal distribution, two mixed normal distributions and four…
Descriptors: Correlation, Mathematical Formulas, Statistical Distributions, Statistical Significance
Dealing with Nonnormal Data: Parametric Analysis of Transformed Data vs Nonparametric Analysis.
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Rasmussen, Jeffrey Lee; Dunlap, William P. – Educational and Psychological Measurement, 1991
Results of a Monte Carlo study with 4 populations (3,072 conditions) indicate that when distributions depart markedly from normality, nonparametric analysis and parametric analysis of transformed data show superior power to parametric analysis of raw data. Under conditions studied, parametric analysis of transformed data is more powerful than…
Descriptors: Comparative Analysis, Computer Simulation, Monte Carlo Methods, Power (Statistics)
Interpreting Significant Left-Tailed Analysis of Variance F-Ratios.
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Shine, Lester C., II – Educational and Psychological Measurement, 1982
The interpretation of significant left-tailed analysis of variance (ANOVA) F-ratios is supported by considering the case of a fixed effects ANOVA model. The conclusions of this case are generalizable to other standard ANOVA models. (Author/PN)
Descriptors: Analysis of Variance, Data Analysis, Hypothesis Testing, Mathematical Models
Combining Probabilities from Discrete Probability Distributions.
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Edgington, Eugene S.; Haller, Otto – Educational and Psychological Measurement, 1984
This paper explains how to combine probabilities from discrete distributions, such as probability distributions for nonparametric tests. (Author/BW)
Descriptors: Computer Software, Data Analysis, Hypothesis Testing, Mathematical Formulas