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Vaske, Jerry J. – Sagamore-Venture, 2019
Data collected from surveys can result in hundreds of variables and thousands of respondents. This implies that time and energy must be devoted to (a) carefully entering the data into a database, (b) running preliminary analyses to identify any problems (e.g., missing data, potential outliers), (c) checking the reliability and validity of the…
Descriptors: Surveys, Theories, Hypothesis Testing, Effect Size
Schumacker, Randall E. – 1989
The relationship of multiple linear regression to various multivariate statistical techniques is discussed. The importance of the standardized partial regression coefficient (beta weight) in multiple linear regression as it is applied in path, factor, LISREL, and discriminant analyses is emphasized. The multivariate methods discussed in this paper…
Descriptors: Comparative Analysis, Discriminant Analysis, Equations (Mathematics), Factor Analysis
Peer reviewedO'Brecht, Michael; And Others – Research in Higher Education, 1989
Survey data from 458 former health science graduate students were examined for correlations between variables that might be used in selecting research training award recipients and successful training outcome defined as a highly productive research career. Four variables that showed promise as useful indicators of posttraining research are…
Descriptors: Academic Achievement, Discriminant Analysis, Factor Analysis, Grades (Scholastic)

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