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Yan Zhou – ProQuest LLC, 2021
As the international large-scale assessments (ILSAs) become more popular, policy makers and education practitioners are interested in collecting as much student background information as possible to better understand the learning context of their students. To collect such abundant information, administrators need to develop a lot of questions.…
Descriptors: Matrices, Sampling, Research Design, Questionnaires
Spearing, Debra; Woehlke, Paula – 1989
To assess the effect on discriminant analysis in terms of correct classification into two groups, the following parameters were systematically altered using Monte Carlo techniques: sample sizes; proportions of one group to the other; number of independent variables; and covariance matrices. The pairing of the off diagonals (or covariances) with…
Descriptors: Classification, Correlation, Discriminant Analysis, Matrices

Miller, John K. – Multivariate Behavioral Research, 1975
Descriptors: Correlation, Goodness of Fit, Hypothesis Testing, Matrices
Hummel, Thomas J.; Feltovich, Paul J. – 1974
In some correlational studies it is not reasonable to assume that bivariate observations are uncorrelated. An example would be a configural analysis in which two individuals are correlated across several variables (e.g., Q-technique). The present study was a Monte Carlo investigation of the robustness of techniques used in judging the magnitude of…
Descriptors: Computer Programs, Correlation, Hypothesis Testing, Matrices

Carroll, Robert M. – Educational and Psychological Measurement, 1976
Examines the similarity between the coordinates which resulted when correlations were used as similarity measures and the factor loadings obtained by factor analyzing the same correlation matrix. Real data, a set of error free data, and some computer generated data containing deliberately introduced sampling error are analyzed. (RC)
Descriptors: Comparative Analysis, Correlation, Data Analysis, Factor Analysis