An alternative approach for introducing instrumental variables in econometrics courses is presented in this article. The method is based on the ordinary least squares omitted variable bias formula. The intuition for the approach capitalizes on students' understanding and intuition of omitted variables. Thus, if students understand omitted variable…

Within psychology and the social sciences, Ordinary Least Squares (OLS) regression is one of the most popular techniques for data analysis. In order to ensure the inferences from the use of this method are appropriate, several assumptions must be satisfied, including the one of constant error variance (i.e. homoskedasticity). Most of the training…

Percentage of body fat, age, weight, height, and 14 circumference measurements (e.g., waist) are given for 184 women aged 18-25. Body fat, one measure of health, was accurately determined by an underwater weighing technique which requires special equipment and training of the individuals conducting the process. Modeling body fat percentage using…

Discusses the use and interpretation of multiple regression analysis with computer programs and presents a flow chart of the process. A general explanation of the flow chart is provided, followed by an example showing the development of a linear equation which could be used in estimating manufacturing overhead cost. (Author/LRW)

The problem of fitting a surge function to a set of data such as that for a drug response curve is considered. A variety of different techniques are applied, including using some fundamental ideas from calculus, the use of a CAS package, and the use of Excel's regression features for fitting a multivariate linear function to a set of transformed…

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)