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Xian, Sidong; Xia, Haibo; Yin, Yubo; Zhai, Zhansheng; Shang, Yan – Cogent Education, 2016
Teaching quality is the lifeline of the higher education. Many universities have made some effective achievement about evaluating the teaching quality. In this paper, we establish the Students' evaluation of teaching (SET) discriminant analysis model and algorithm based on principal component clustering analysis. Additionally, we classify the SET…
Descriptors: Discriminant Analysis, Factor Analysis, Student Evaluation of Teacher Performance, Instructional Effectiveness
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Rindskopf, David; Rose, Tedd – Multivariate Behavioral Research, 1988
Confirmatory factor analysis was applied to test second- and higher-order factor models in the areas of structure of abilities, allometry, and the separation of specific and error variance estimates. The estimation of validity and reliability, second-order models within factor analysis models, and the concept of discriminability were also studied.…
Descriptors: Discriminant Analysis, Error of Measurement, Estimation (Mathematics), Factor Analysis
Baratta, Mary Kathryne – 1979
The advantages of the Delphi Technique are that it relies on collective expert judgment, prevents the excessive influence in decision-making of those in positions of status, and encourages consensus. The technique consists of five steps: (1) asking experts to list items relevant to a topic; (2) returning the list to the participants and asking…
Descriptors: Administration, Decision Making, Discriminant Analysis, Factor Analysis
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Larsson, Bernt – 1974
This report gives some simple examples of stability for one factor and 2 x 2 factorial analysis of variance, reliability and correlations. The findings are very different: from superstability (no transformation whatsoever can change the result) to almost total instability. This is followed by a discussion of applications to multivariate analysis,…
Descriptors: Analysis of Variance, Correlation, Discriminant Analysis, Factor Analysis
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Hofmann, Richard J. – 1971
The primary objectives of this paper are pedagogical: to provide a reliable semi-subjective transformation procedure that might be used without difficulty by beginning students in factor analysis; to clarify and extend the existing knowledge of oblique transformations in general; and to provide a brief but meaningful explication of the general…
Descriptors: Discriminant Analysis, Factor Analysis, Mathematical Applications, Mathematical Models
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
Huberty, Carl J. – 1971
This study was concerned with various schemes for reducing the number of variables in a multivariate analysis. Two sets of illustrative data were used; the numbers of criterion groups were 3 and 5. The proportion of correct classifications was employed as an index of discriminatory power of each subset of variables selected. Of the four procedures…
Descriptors: Cluster Analysis, Correlation, Criteria, Discriminant Analysis