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 user-supplied 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 R2.)

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.

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 -
Department of Economics, SUNY-Oswego, Oswego, NY 13126