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Braham, Hana Manor; Ben-Zvi, Dani – Statistics Education Research Journal, 2017
A fundamental aspect of statistical inference is representation of real-world data using statistical models. This article analyzes students' articulations of statistical models and modeling during their first steps in making informal statistical inferences. An integrated modeling approach (IMA) was designed and implemented to help students…
Descriptors: Foreign Countries, Elementary School Students, Statistical Inference, Mathematical Models
Wilcox, Rand R. – Educational and Psychological Measurement, 2006
Consider the nonparametric regression model Y = m(X)+ [tau](X)[epsilon], where X and [epsilon] are independent random variables, [epsilon] has a median of zero and variance [sigma][squared], [tau] is some unknown function used to model heteroscedasticity, and m(X) is an unknown function reflecting some conditional measure of location associated…
Descriptors: Nonparametric Statistics, Mathematical Models, Regression (Statistics), Probability
Levine, Douglas W.; Rockhill, Beverly – Teaching Statistics: An International Journal for Teachers, 2006
We focus on the problem of ignoring statistical independence. A binomial experiment is used to determine whether judges could match, based on looks alone, dogs to their owners. The experimental design introduces dependencies such that the probability of a given judge correctly matching a dog and an owner changes from trial to trial. We show how…
Descriptors: Probability, Statistical Analysis, Hypothesis Testing, Mathematical Models
Davison, Mark L. – 1981
The interest in developmental sequences and learning hierarchies is growing. One approach to the study of such sequences is to gather data on several variables, each of which corresponds to a stage, step, or phase in the sequence and to examine the associations between the variables as displayed in a contingency table. If the variables are…
Descriptors: Cognitive Development, Hypothesis Testing, Mathematical Models, Probability

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
Werts, Charles E.; And Others – 1971
To resolve a recent controversy between Klein and Cleary and Levy, a model for dichotomous congeneric items is presented which has mean errors of zero, dichotomous true scores that are uncorrelated with errors, and errors that are mutually uncorrelated. (Author)
Descriptors: Correlation, Hypothesis Testing, Mathematical Models, Mathematics
Toothaker, Larry E. – 1972
The area investigated in the present study is the comparison of the permutation t-test with Student's t-test and the Mann-Whitney U-test. The comparison was made for small samples for three distributions, including a normal distribution, a uniform distribution, and a skewed distribution. The properties of each test compared were the probability of…
Descriptors: Comparative Analysis, Hypothesis Testing, Mathematical Models, Probability
Pena, Deagelia M. – 1972
One approach to the problem of analyzing classroom interaction by use of a Markoff chain is presented. The two sections of the paper present (1) a discusion of Hoel's test of order of a Markoff chain, and a Likelihood Ratio Criterion (LRC) for a two-dependent Markoff chain is given, and (2) a discussion of possible adjustments of Darwin's LRC with…
Descriptors: Data Analysis, Hypothesis Testing, Interaction Process Analysis, Mathematical Models

Wilcox, Rand R. – Journal of Educational Statistics, 1984
Two stage multiple-comparison procedures give an exact solution to problems of power and Type I errors, but require equal sample sizes in the first stage. This paper suggests a method of evaluating the experimentwise Type I error probability when the first stage has unequal sample sizes. (Author/BW)
Descriptors: Hypothesis Testing, Mathematical Models, Power (Statistics), Probability
Klockars, Alan J.; Hancock, Gregory R. – 1993
The challenge of multiple comparisons is to maximize the power for answering specific research questions, while still maintaining control over the rate of Type I error. Several multiple comparison procedures have been suggested to meet this challenge. The stagewise protected procedure (SPP) of A. J. Klockars and G. R. Hancock tests null hypotheses…
Descriptors: Comparative Analysis, Computer Simulation, Hypothesis Testing, Mathematical Models

Holt, D. – Sociological Methods and Research, 1979
Two techniques for interpretation of fitted log-linear models in contingency table analysis are discussed. The use of odds ratios as opposed to direct interpretation of the fitted model is argued for. (Author/JKS)
Descriptors: Expectancy Tables, Goodness of Fit, Hypothesis Testing, Mathematical Models
Parshall, Cynthia G.; And Others – 1995
Contingency tables, and their associated statistical tests, are frequently used in educational and social research. Popular statistical tests used in contingency table analyses include the Pearson chi-square test and the likelihood ratio chi-square test. These two tests are chi-square distributed under large sample conditions. However, when a…
Descriptors: Chi Square, Comparative Analysis, Estimation (Mathematics), Hypothesis Testing

Viana, Marlos A. G. – Journal of Educational Statistics, 1991
A Bayesian solution is suggested to the problem of jointly estimating "k is greater than 1" binomial parameters in conjunction with the problem of testing, in a Bayesian sense, the hypothesis "H" of parametric homogeneity. Applications of the estimates are illustrated with several types of data, including ophthalmological…
Descriptors: Bayesian Statistics, Elementary Secondary Education, Equations (Mathematics), Higher Education
Wilcox, Rand R. – 1979
Three separate papers are included in this report. The first describes a two-stage procedure for choosing from among several instructional programs the one which maximizes the probability of passing the test. The second gives the exact sample sizes required to determine whether a squared multiple correlation coefficient is above or below a known…
Descriptors: Bayesian Statistics, Correlation, Hypothesis Testing, Mathematical Models
Lai, Morris K. – 1974
When analysis of variance is used, statistically significant differences may or may not be of practical significance to educators. A large part of the problem is due to the fact that a "zero difference" null hypothesis can always be rejected statistically if the sample size is large enough. If, however, a method based on the noncentral F…
Descriptors: Analysis of Variance, Data Analysis, Hypothesis Testing, Mathematical Models