Arc

Arc is an Xlisp-Stat application for the analysis of regression models that study the dependence of a response on a set of predictors. Most of the methodology in the basic Arc is based and described on the book, Applied Regression Including Computing and Graphics, by R. D. Cook and Sanford Weisberg, of the University of Minnesota.

Arc is a user-friendly program designed specifically for use while studying this material, and for applying the ideas learned to other data sets. The program permits the user to perform the diverse analysis methods as discussed in the book easily and quickly. Regression is one of the fundamental tools of data analysis. It is the study of how a response variable depends on one or more predictors.

The mathematical level required to use the software is intentionally low; maybe the basic knowledge of statistical methods. Arc features many easily used graphical methods, most based on simple two-dimensional scatterplots that provide analysts with more insight into their data than would have been possible impossible or at best difficult to implement using standard statistical software packages.

Multiple Linear Regression function features standard linear models, starting with simple regression, with the basics of graphics, including 2D and 3D scatterplots and scatterplot matrices. It lets you use graphs to better understand regression problems in which no model is available, and as the basis for diagnostic methods. Arc is available on the internet for free download on the book’s website at the address given in the Appendix.

Arc software versions are available for Mac, Linux/Unix, and Windows devices. Any changes, updates, and other support documentation are also available on the Arc software’s website. Arc can also be extended using the Xlisp-Stat program to add new functionalities such as new smoothers, new fitting methods, new menu items, and more.