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Logistic Regression: Modeling with StatTools
Lichtendahl, Kenneth C. Jr.; Andrasko, Joe; Boatright, Benjamin Technical Note QA-0945 / Published June 12, 2023 / 6 pages.
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Logistic regression is a modeling technique often used to predict a binary variable—a variable coded as 1 if an event of interest occurs (e.g., a borrower defaults on a loan) and coded as 0 otherwise. This note details how logistic regression applies the logistic function to generate a probability forecast for a binary event. It also includes an example of how to fit a logistic regression model to loan default data using StatTools (an Excel add-in). The StatTools output is then used to predict a loan’s default as a function of the borrower’s credit score.




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  • Overview

    Logistic regression is a modeling technique often used to predict a binary variable—a variable coded as 1 if an event of interest occurs (e.g., a borrower defaults on a loan) and coded as 0 otherwise. This note details how logistic regression applies the logistic function to generate a probability forecast for a binary event. It also includes an example of how to fit a logistic regression model to loan default data using StatTools (an Excel add-in). The StatTools output is then used to predict a loan’s default as a function of the borrower’s credit score.

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