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
Learn to use tools from the Bioconductor project to perform analysis of genomic data. This is the fifth course in the Genomic Big Data Specialization from Johns Hopkins University.Created by: Johns... more
R Programming CapstoneCreated by: Johns Hopkins University more
Understanding how to eat healthy can be daunting, especially when presented with unfamiliar science. Learn and apply everyday nutrition concepts to your lifestyle to get the most out of what you... more
This specialization prepares students for the global challenges that businesses face in the 21st century. The global marketplace now and in the future spans emerging markets, a world connected by... more
Welcome to the \"Cross-Functional Collaboration\" course! This course focuses on the principles and strategies for collaborating effectively with colleagues from different functional areas. Through... more
Powered by
