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Burdenski, Thomas K., Jr. – 2000
This paper reviews graphical and nongraphical procedures for evaluating multivariate normality by guiding the reader through univariate and bivariate procedures that are necessary, but insufficient, indications of a multivariate normal distribution. A data set using three dependent variables for two groups provided by D. George and P. Mallery…
Descriptors: Graphs, Multivariate Analysis, Statistical Distributions
George, Carrie A. – 2001
Multivariate techniques have been implemented with greater and greater frequency. In order to use multivariate techniques researchers must understand the fundamental assumptions. The purpose of this paper is to evaluate one of the assumptions of multivariate analysis, normality. Overall, normal distributions are unimodal and symmetrical, and they…
Descriptors: Estimation (Mathematics), Evaluation Methods, Multivariate Analysis, Statistical Distributions
Randolph, Justus J. – Online Submission, 2005
Fleiss' popular multirater kappa is known to be influenced by prevalence and bias, which can lead to the paradox of high agreement but low kappa. It also assumes that raters are restricted in how they can distribute cases across categories, which is not a typical feature of many agreement studies. In this article, a free-marginal, multirater…
Descriptors: Multivariate Analysis, Statistical Distributions, Statistical Bias, Interrater Reliability
Jarrell, Michele G. – 1991
A probability distribution was developed for the Andrews-Pregibon (AP) statistic. The statistic, developed by D. F. Andrews and D. Pregibon (1978), identifies multivariate outliers. It is a ratio of the determinant of the data matrix with an observation deleted to the determinant of the entire data matrix. Although the AP statistic has been used…
Descriptors: Computer Simulation, Error of Measurement, Matrices, Multivariate Analysis
Jones, Gail – 1989
A brief historical background of discriminant analysis is given, with a description of the variety of roles that discriminant analysis can perform. Focus is on the classification role of discriminant analysis and how it can be performed by using Fisher's classification functions or the canonical discriminant functions. A small hypothetical data…
Descriptors: Classification, Discriminant Analysis, Literature Reviews, Multivariate Analysis
Harwell, Michael; Serlin, Ronald – 1995
A Monte Carlo study was used to examine the Type I error rates of five multivariate tests for the single-factor repeated measures model. The performance of Hotelling's T-squared and four nonparametric tests, including a chi-square and an "F" test version of a rank-transform procedure, was investigated for different distributions, sample…
Descriptors: Chi Square, Error of Measurement, Monte Carlo Methods, Multivariate Analysis
Kromrey, Jeffrey D.; Blair, R. Clifford – 1991
New multivariate permutation tests are proposed that may be effectively substituted for Hotelling's T-Square test in situations commonly arising in educational research. The new tests: (1) are distribution-free; (2) provide tests of directional as well as non-directional hypotheses; (3) may be tailored for sensitivity to specific treatment…
Descriptors: Educational Research, Equations (Mathematics), Hypothesis Testing, Mathematical Models
Friedman, Larry P. – 1984
Few methods have been tried and used to graphically represent more than two variables. This poster session showed a new method for representing three continuous variables on a single scatterplot using the THREEDE computer program. Two variables are represented as a normal bivariate distribution. The third variable is represented by a symbol, e.g.…
Descriptors: Computer Graphics, Computer Software, Correlation, Data Analysis
Kirisci, Levent; Hsu, Tse-Chi – 1993
Most of the multivariate statistical techniques rely on the assumption of multivariate normality. The effects of non-normality on multivariate tests are assumed to be negligible when variance-covariance matrices and sample sizes are equal. Therefore, in practice, investigators do not usually attempt to remove non-normality. In this simulation…
Descriptors: Computer Simulation, Equations (Mathematics), Mathematical Models, Matrices