Excel is often poorly regarded as a platform for regression analysis. The regression add-in in its Analysis Toolpak has not changed since it was introduced in 1995, and it was a flawed design even back then.  (See this link for a discussion.)    That’s unfortunate, because an Excel file can be a very good place in which to build regression models, compare and refine them, create high-quality editable tables and charts, share and present the results, and teach regression to those constituencies of students and practitioners for whom Excel is the only analytic tool they may ever use on a regular basis.

Over the last 10 years I’ve developed an alternative, a free add-in called RegressIt, which is designed to take maximal advantage of the Excel environment and support good practices of data analysis.  Its home page is regressit.com, and a set of slides that gives a helicopter tour of its features is here.   I’ve used it for teaching an advanced course on regression and time series analysis to grad students in business and engineering, but it’s intended for use in teaching at all levels and in applications.  It was first released to the public in 2014 and has undergone major enhancements recently.  I urge you to take a look and give it a test drive.  It performs both linear and logistic regression in Excel, producing highly interactive model worksheets with well-designed outputs.  It also has some novel tools for navigating the model space, keeping an audit trail, and providing instruction as the user goes along.  The logistic model worksheets are particularly interesting:  they include a lot of tables and charts with spinners that can be used to play with their parameters.  For example, you can dial the cutoff value up and down after fitting a model, while watching what happens in classification tables and tracking your position on the ROC curve.  This feature does not require the program to be running, so  a single model worksheet is a self-contained demonstration tool for properties of a logistic model.  See the Titanic example on the web site.

And… it has an interface with R that allows R to be used as a computational engine for producing results in both environments.   See this short video for a demonstration.  This tool provides more analysis options and allows large data sets to be handled.   The full dataset does not need to fit in Excel.  It suffices to have matching variable names there. This allows Excel to…

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