Studies comparing virtual and physical manipulative environments (VME and PME) in inquiry-based science learning have mostly focused on students' learning outcomes but not on the actual processes they engage in during the learning activities. In this paper, we examined experimentation strategies in an inquiry activity and their relation to…

Variable selection techniques in stepwise regression analysis are discussed. In stepwise regression, variables are added or deleted from a model in sequence to produce a final "good" or "best" predictive model. Stepwise computer programs are discussed and four different variable selection strategies are described. These…

The way newspaper quality related to newspaper circulation was examined by asking journalism professionals to list the four best and the four worst daily newspapers with under 200,000 circulation in their own states. Returns were counted in only those states where two or more judges returned ballots. A total of 79 newspapers was rated superior by…

Analysis of variance (ANOVA) and multiple regression are two of the most commonly used methods of data analysis in behavioral science research. Although ANOVA was intended for use with experimental designs, educational researchers have used ANOVA extensively in aptitude-treatment interaction (ATI) research. This practice tends to make researchers…

The extent to which standardized regression coefficients (beta values) can be used to determine the importance of a variable in an equation was explored. The beta value and the part correlation coefficient--also called the semi-partial correlation coefficient and reported in squared form as the incremental "r squared"--were compared for…

An investigation of the effects of randomly missing data in two-predictor regression analyses is described. The differences in the effectiveness of five common treatments of missing data on estimates of R-squared values and each of the two standardized regression weights is also investigated. Bootstrap sample sizes of 50, 100, and 200 were drawn…

The stepwise regression method of selecting predictors for computer assisted multiple regression analysis was compared with forward, backward, and best subsets regression, using 16 data sets. The results indicated the stepwise method was preferred because of its practical nature, when the models chosen by different selection methods were similar…

A Monte Carlo study was performed to test under what conditions and to what degree various alternatives would be superior to multiple linear regression (MLR). The criteria used was the mean squared error of prediction of individual scores and the mean squared error of estimation of the regression weights. Populations were simulated containing…

Several advantages to the use of factor scores as independent variables in a multiple regression equation were found. To help select the most desirable type of factor score on which to calculate a regression equation, computer-based Monte Carlo methods were used to compare the predictive accuracy upon replication of regression of five…

The present paper sought to investigate the usefulness to accountability of identifying outlying schools through multiple regression. The outlier approach identifies schools which differ significantly for reasons other than variation in the predictors. The present study was not able to confirm the construct validity of the outlier approach for the…

The Tutorial Assistance Program (TAP) of the University of California (Irvine) is described and a new method of evaluation is illustrated through an analysis of the performance of students in six large introductory classes. This approach to evaluation starts with a multiple regression equation for predicting course grades of those not in tutoring…

In this study, locus of control and IQ were compared to assess the power of each as a predictor of performance on academic and non-academic tasks. Four locus of control scales: the Intellectual Achievement Responsibility Scale, the Academic Achievement Accountability Questionnaire, the Rotter I-E scale, the Origin-Pawn measure and the Iowa Tests…

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…

This study at Miami University (Ohio) compared multiple regression techniques, traditionally used in higher education to examine salary inequities, with compa-ratio analysis. This new technique has been a corporate practice for reviewing salary and gender bias and is now being applied in studies of higher education salary equity. Weaknesses of the…

Skeletal models of the regression of occupational status on schooling that correct for response variability and incorporate a variance component structure are presented. The models were derived from an analysis which used multiple measurements of educational attainment and occupational status for 518 male high school graduates and their brothers.…