A Teaching Tool for Nonlinear Regression: Visual Fit
Year: 1999
Type: article
Abstract: We describe a Java applet that allows users to see and learn the fitting of regression models in a manner that is both visual and interactive, as well as consonant for linear and nonlinear models. In addition, this program familiarizes users with the fact that many different parameterizations exist for a single function, and it provides insight about the relationship between these models. Called Visual Fit, this program draws scatterplots of data and allows users to fit various nonlinear models to the data. The program can also provide least squares estimates or true population parameters for comparison with the estimates made by the user. We discuss what types of parameters can be represented in a visually obvious way and which cannot. Visual Fit may be useful for both introductory statistics classes and higher-level courses. Visual Fit is available at http://www.amstat.org/publications/jse/secure/v7n2/visualfit.html
Source: Journal of Statistics Education
Authors: Ying Taur, Charles E. McCulloch
Institution: Cornell University
Language: English
Subfield: Statistics and Probability
Field: Mathematics
Domain: Physical Sciences
Open Access status: gold
Estimated APC paid: $1,134
OpenAlex ID: W4291474079