Logistic Regression and Prediction for Health Data

About this Course

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.

Created by: University of Michigan


Related Online Courses

This Advanced Kubernetes course is designed for experienced Kubernetes administrators, DevOps engineers, software developers, cloud architects, and IT professionals seeking to enhance their... more
Leadership for Public Health Crises will enable current and prospective managers, directors, unit heads, and elected officials to effectively lead their organizational response to profound... more
This Specialization is intended for post-graduate students seeking to develop effective communication skills. Through a series of courses, you will cover key topics such as audience analysis,... more
In questi corsi acquisirai dimestichezza con l\'infrastruttura flessibile di Google Cloud e i servizi della piattaforma, concentrandoti in modo specifico su Compute Engine. In questa sessione viene... more
In this course students learn the basic concepts of acoustics and electronics and how they can applied to understand musical sound and make music with electronic instruments. Topics include: sound... more

CONTINUE SEARCH

FOLLOW COLLEGE PARENT CENTRAL