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 comprehensive course provides a deep dive into Express.js, a robust web application framework for Node.js. Participants will master fundamental concepts, architecture, and the step-by-step... more
HTML is at the very core of the world wide web, it is the language in which all web pages are written and rendered. In this 75 minute long project you will build knowledge base for your business,... more
This specialization is intended for people who are interested in taking their web development with Django to the next level. It is assumed that learners have are familiar with Python and have taken... more
Backend refers to the server side of development. Here, the primary focus is on how a website works. Node.js is considered efficient for the development of backend applications as it brings... more
This Guided Project, Introduction to D3.js is for those who want to learn about D3.js which is a JavaScript library for producing SVG-based, dynamic, interactive data visualizations in web... more

CONTINUE SEARCH

FOLLOW COLLEGE PARENT CENTRAL