This course introduces learners to the analysis of binary/dichotomous outcomes. Learners will become familiar with fundamental tests for two-group comparisons and statistical inference plus prediction more broadly using logistic regression. They will understand the connection between prevalence, risk ratios, and odds ratios. By the end of this course, learners will be able to understand how binary outcomes arise, how to use R to compare proportions between two groups, how to fit logistic regressions in R, how to make predictions using logistic regression, and how to assess the quality of these predictions. All concepts taught in this course will be covered with multiple modalities: slide-based lectures, guided coding practice with the instructor, and independent but structured exercises.
Why Do We Need to Assess Predictions?
Loading...
Skills You'll Learn
Probability And Statistics, Data Analysis, Statistical Modeling, Statistical Analysis, Logistic Regression
From the lesson
Assessing the Predictive Accuracy of Logistic Regression Models
This module introduces you to tools for assessing the quality of a fitted logistic regression model.
Taught By
Philip S. Boonstra
Associate Professor
Bhramar Mukherjee
John D Kalbfleisch Distinguished Professor