Chapter 4: Bivariate Regression Model
Related links:
 The CUWU Statistics Program
 This page contains a collection of online java applets written by John Marden (supported by grants from the
National Science Foundation and the Sloan Center for Asynchronous Learnings Environments). The data analysis
applet provides basic sample statistics, histograms, scatterplots, and a graphical depiction of a bivariate
regression line for a variety of data sets or usersupplied data.
 Components of r
(Rice Virtual Lab in Statistics)
 This Java applet illustrates the decomposition of the variance of a bivariate regression model into
explained and unexplained components. Try changing the slope, the standard deviation of the X's and the
standard deviation of the estimate to see how each of these effects the correlation coefficient between X and
Y. (Notes: The standard error of the estimate is the standard deviation of the error term and Pearson's r is
the square root of R^{2}.)
 Regression Applet
(by R. Webster West)
 This applet illustrates the effect of adding an observation to a regression when the sample size is small. It illustrates how sensitive regression estimates can be to the presence of outliers in small samples.
 FR 5218  Regression Refresher
 This site, designed to accompany Thomas E. Burk's course on "Assessment and Modeling of Forests" at the
University of Minnesota, contains a solid discussion of the bivariate regression model. A
brief discussion of multiple regression and nonlinear regression methods also appears on this site.
 STATLETS
 A statistical package consisting of a collection of Java applets. A student edition that allows the
estimation of models with up to 10 variables and 100 observations may be accessed over the internet or may be
downloaded for free from this site. This package estimates basic regression models.
 Egwald Statistics  Multiple Regression
 This online regression package, created by Elmer G. Wiens, allows the user to estimate multiple regression
models online (including models with parameter restrictions).
John Kane  kane@oswego.edu
Department of Economics, SUNYOswego, Oswego, NY 13126
