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Showing 1 to 15 of 16 results Save | Export
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Taylor, Laura; Doehler, Kirsten – Journal of Statistics Education, 2015
This paper examines the use of a randomization-based activity to introduce the ANOVA F-test to students. The two main goals of this activity are to successfully teach students to comprehend ANOVA F-tests and to increase student comprehension of sampling distributions. Four sections of students in an advanced introductory statistics course…
Descriptors: Sampling, Statistical Distributions, Statistical Analysis, Mathematics Activities
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Quinino, Roberto C.; Reis, Edna A.; Bessegato, Lupercio F. – Teaching Statistics: An International Journal for Teachers, 2013
This article proposes the use of the coefficient of determination as a statistic for hypothesis testing in multiple linear regression based on distributions acquired by beta sampling. (Contains 3 figures.)
Descriptors: Multiple Regression Analysis, Hypothesis Testing, Sampling, Statistical Distributions
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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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Lunneborg, Clifford E.; Tousignant, James P. – Multivariate Behavioral Research, 1985
This paper illustrates an application of Efron's bootstrap to the repeated measures design. While this approach does not require parametric assumptions, it does utilize distributional information in the sample. By appropriately resampling from study data, the bootstrap may determine accurate sampling distributions for estimators, effects, or…
Descriptors: Hypothesis Testing, Research Design, Research Methodology, Sampling
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Anderson, Harry E., Jr.; And Others – Journal of Experimental Education, 1984
A sampling subspace in hypothesis testing where Type II error is made for completely illogical reasons from the standpoint of probability is described. The case of unequal probabilities of populations or conditions is also considered. (Author/BS)
Descriptors: Hypothesis Testing, Maximum Likelihood Statistics, Probability, Sampling
Kennedy, Charlotte A. – 2002
The use of and emphasis on statistical significance testing has pervaded educational and behavioral research for many decades in spite of criticism by prominent researchers in this field. Much of the controversy is caused by lack of understanding or misinterpretations. This paper reviews criticisms of statistical significance testing and discusses…
Descriptors: Educational Research, Hypothesis Testing, Research Methodology, Sampling
Yu, Chong Ho; And Others – 1995
Central limit theorem (CLT) is considered an important topic in statistics, because it serves as the basis for subsequent learning in other crucial concepts such as hypothesis testing and power analysis. There is an increasing popularity in using dynamic computer software for illustrating CLT. Graphical displays do not necessarily clear up…
Descriptors: Computer Simulation, Computer Software, Hypothesis Testing, Identification
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Zimmerman, Donald W. – Journal of Experimental Education, 1986
A computer program randomly sampled ordered pairs of scores from known populations that departed from bivariate normal form and calculated correlation coefficients from sample values. Hypotheses were tested (1) that population correlations are zero using the t statistic; and (2) that population correlations have non-zero values using the r to z…
Descriptors: Correlation, Hypothesis Testing, Sampling, Statistical Distributions
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Alsawalmeh, Yousef M.; Feldt, Leonard S. – Applied Psychological Measurement, 1992
An approximate statistical test is derived for the hypothesis that the intraclass reliability coefficients associated with two measurement procedures are equal. Control of Type 1 error is investigated by comparing empirical sampling distributions of the test statistic with its derived theoretical distribution. A numerical illustration is…
Descriptors: Equations (Mathematics), Hypothesis Testing, Mathematical Models, Measurement Techniques
Olejnik, Stephen F.; Algina, James – 1985
The present investigation developed power curves for two parametric and two nonparametric procedures for testing the equality of population variances. Both normal and non-normal distributions were considered for the two group design with equal and unequal sample frequencies. The results indicated that when population distributions differed only in…
Descriptors: Computer Simulation, Hypothesis Testing, Power (Statistics), Sampling
McLean, James E. – 1983
This simple method for simulating the Central Limit Theorem with students in a beginning nonmajor statistics class requires students to use dice to simulate drawing samples from a discrete uniform distribution. On a chalkboard, the distribution of sample means is superimposed on a graph of the discrete uniform distribution to provide visual…
Descriptors: Higher Education, Hypothesis Testing, Research Methodology, Sampling
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Rasmussen, Jeffrey Lee – Evaluation Review, 1985
A recent study (Blair and Higgins, 1980) indicated a power advantage for the Wilcoxon W Test over student's t-test when calculated from a common mixed-normal sample. Results of the present study indicate that the t-test corrected for outliers shows a superior power curve to the Wilcoxon W.
Descriptors: Computer Simulation, Error of Measurement, Hypothesis Testing, Power (Statistics)
Breunig, Nancy A. – 1995
Despite the increasing criticism of statistical significance testing by researchers, particularly in the publication of the 1994 American Psychological Association's style manual, statistical significance test results are still popular in journal articles. For this reason, it remains important to understand the logic of inferential statistics. A…
Descriptors: Computer Uses in Education, Educational Research, Hypothesis Testing, Sampling
Lunneborg, Clifford E. – 1983
The wide availability of large amounts of inexpensive computing power has encouraged statisticians to explore many approaches to a basis for inference. This paper presents one such "computer-intensive" approach: the bootstrap of Bradley Efron. This methodology fits between the cases where it is assumed that the form of the distribution…
Descriptors: Analysis of Variance, Error of Measurement, Estimation (Mathematics), Hypothesis Testing
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Olejnik, Stephen F.; Algina, James – 1985
This paper examined the rank transformation approach to analysis of variance as a solution to the Behrens-Fisher problem. Using simulation methodology four parameters were manipulated for the two group design: (1) ratio of population variances; (2) distribution form; (3) sample size and (4) population mean difference. The results indicated that…
Descriptors: Analysis of Variance, Computer Simulation, Error of Measurement, Hypothesis Testing
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