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McCabe, George P.; McCabe, Sharron A.S. – Multiple Linear Regression Viewpoints, 1980
A statistical technique designed to highlight the contributions of two continuous predictor variables to a continuous criterion variable is described. The technique involves selecting subpopulations, called pockets, via regression techniques. An example using cognitive styles to predict performance on problem-solving tasks is discussed.…
Descriptors: Analysis of Variance, Classification, Cognitive Style, Data Analysis

Rock, Donald A.; And Others – Multivariate Behavioral Research, 1978
Systematic procedures are outlined for testing the assumption made on the dependent variables in a variety of statistical techniques. Specifically, procedures are outlined for testing the assumption that the dependent variables are measuring the same constructs in the same metrics with equivalent reliabilities across all subgroups. (Author/JKS)
Descriptors: Analysis of Covariance, Analysis of Variance, Discriminant Analysis, Higher Education

Serlin, Ronald C.; Levin, Joel R. – Journal of Educational Statistics, 1985
Multiple linear regression is a versatile model for encompassing analysis of variance, analysis of covariance, and aptitude-by-treatment interaction designs. The questions of how to teach the coding of levels of a qualitative variable is addressed in this paper. (Author/LMO)
Descriptors: Analysis of Covariance, Analysis of Variance, Higher Education, Multiple Regression Analysis

St. Pierre, Suzanne; Olsen, Larry K. – American Journal of Distance Education, 1991
Describes a study that was conducted to analyze students' perceptions of instructors and instructional impact in terms of student satisfaction with the delivery of college credit correspondence courses at Pennsylvania State University. The development and use of a student satisfaction measure, the Student Perception Questionnaire, is also…
Descriptors: Analysis of Variance, Attitude Measures, Correspondence Study, Distance Education

And Others; Roll, Steve – Multiple Linear Regression Viewpoints, 1979
A Type VI error results from inconsistency between the researchers' question of interest and the statistical procedures employed to analyze the data. An example of a research problem is analyzed to show the increase in statistical power resulting from improved research design, using multiple regression instead of analysis of variance. (CTM)
Descriptors: Analysis of Variance, Error Patterns, Higher Education, Hypothesis Testing
Keyton, Joann – 1989
This study investigated William Schutz's three-dimensional theory of interpersonal behavior and compatibility (FIRO) to determine its validity as a group measure of compatibility. Data were collected from 248 students enrolled in a multi-section course in small group communications at a large midwestern university. Subjects self-selected…
Descriptors: Analysis of Variance, Attitude Measures, Communication Research, Group Behavior
Williams, John D. – 1976
Before implementing a course in the analysis of variance (ANOVA) taught through multiple linear regression, several concerns must be addressed. Adequate computer facilities that are available to students on a low-cost or cost-free basis are necessary; also students must be able to meaningfully communicate with their major advisor regarding their…
Descriptors: Analysis of Covariance, Analysis of Variance, Computer Assisted Instruction, Costs
Chen, Guo-Ming – 1991
A study examined the relationships between self-disclosure and perceived intercultural effectiveness. Subjects, 129 foreign students from Asia attending a large midwestern university and a large eastern university in the United States, completed two sets of questionnaires. Results from Pearson product-moment correlation, canonical analysis, and…
Descriptors: Analysis of Variance, Communication Research, Communication Skills, Correlation

Marsh, Herbert W. – American Educational Research Journal, 1982
Differences in ratings of the same instructor teaching the same course on two different occasions are related to differences in background characteristics: (1) higher levels of workload/difficulty, (2) higher expected grades, and (3) instructor experience. (PN)
Descriptors: Analysis of Variance, Difficulty Level, Educational Environment, Higher Education
Taylor, Robert L.; And Others – 1973
Mathematical models of judgment policy are compared in evaluating 625 Cadet Performance Reports during a single rating cycle. Linear and nonlinear regressions are used to describe the cues most important in determining overall ratings. In addition, performance rating policy is compared with stated policy for each of forty cadet raters. In general,…
Descriptors: Analysis of Variance, Comparative Analysis, Decision Making, Higher Education

Oman, Paul W. – AEDS Journal, 1986
Describes a study of 38 students at Eastern Oregon State College which identified mathematics proficiency as the key student characteristic leading to successful completion of computer science courses, and developed a model that accounts for 82 percent of the variation in students' final grades in computer courses for use by advisers. (LRW)
Descriptors: Academic Achievement, Academic Advising, Analysis of Variance, Computer Science Education
Lolli, Anthony, Jr.; Owen, Steven V. – 1976
Two issues in the controversy over the use, interpretation, validity, and relevance of student ratings are explored here: the definition of preferred teacher behavior in terms of the rating instrument used, and the relationship between the student's expected grade, grade point average, and the ratings recorded. The objectives of the present…
Descriptors: Analysis of Variance, Check Lists, College Faculty, College Students