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Jerome, Lawrence – Mathematics and Computer Education, 2011
As anyone who has taught or taken a statistics course knows, statistical calculations can be tedious and error-prone, with the details of a calculation sometimes distracting students from understanding the larger concepts. Traditional statistics courses typically use scientific calculators, which can relieve some of the tedium and errors but…
Descriptors: Textbooks, Visual Learning, Graphs, Hypothesis Testing
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Jasien, Paul G. – Journal of Chemical Education, 2008
A semi-quantitative model has been developed to estimate the relative effects of dispersion, dipole-dipole interactions, and H-bonding on the normal boiling points ("T[subscript b]") for a subset of simple organic systems. The model is based upon a statistical analysis using multiple linear regression on a series of straight-chain organic…
Descriptors: Organic Chemistry, Multiple Regression Analysis, Statistical Analysis, Misconceptions
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Dunn, Richard – Journal of Geography in Higher Education, 1989
Points out reasons for using graphical methods to teach simple and multiple regression analysis. Argues that a graphically oriented approach has considerable pedagogic advantages in the exposition of simple and multiple regression. Shows that graphical methods may play a central role in the process of building regression models. (Author/LS)
Descriptors: Geography Instruction, Graphs, Higher Education, Models
Hsiao, Mei-Chu W. – Collegiate Microcomputer, 1985
Describes a course which uses integrated electronic spreadsheets for computer assisted instruction in teaching multiple regression analysis. The process of implementing the method is explained, tips on worksheet arrangement are given, and advantages of using electronic spreadsheets are delineated. (Author/MBR)
Descriptors: Computer Assisted Instruction, Economics Education, Higher Education, Instructional Design
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Maeshiro, Asatoshi – Journal of Economic Education, 1996
Rectifies the unsatisfactory textbook treatment of the finite-sample proprieties of estimators of regression models with a lagged dependent variable and autocorrelated disturbances. Maintains that the bias of the ordinary least squares estimator is determined by the dynamic and correlation effects. (MJP)
Descriptors: Causal Models, Correlation, Economics Education, Heuristics