Logistic Regression

Last updated on Jun 27, 2021
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Logistic Regression

Overview

In regression analysis, logistic regression is an important statistical model that can help model/predict binary dependent variables. An important step in creating logistic regression models is choosing the appropriate threshold, which is done through the ROC Curve. In this app you will explore the ROC curve, decision-making thresholds, and corresponding confusion matrices.

Learning Goals

  1. Understand the logistic regression equation.

  2. Examine the ROC curve and how it can be used to determine a decision-making threshold.

  3. Obtain the confusion matrix for a given decision-making threshold, and use the matrix to calculate sensitivity, specificity, and error rates.

This app was originally developed by Joe Choo in Summer 2020 and further updated by Emmanuel Mokel in Spring 2021.

regression

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