Regression Models in Healthcare

Overview

In this course, you will begin learning about more advanced multivariate statistical methods that are regularly used in healthcare data analysis. You will also practice applying these statistical methods to examples from the healthcare industry. The topics covered in this course will prepare you for interpreting data and making data-informed decisions in real-world healthcare settings. While the course focuses on application and the use of these statistical methods, there is some discussion of the mathematical underpinning, relevant formulae, and assumptions necessary for understanding the application of statistical methods.

This self-paced course is comprised of written content, video content, step-by-step follow-along activities, and assessments to reinforce your learning (Assessments available to Verified Track learners only).

The course is comprised of 4 modules that you should complete in order, as each subsequent module builds on the previous one.

Module 1: Non-Linear Trends
Module 2: Interacting Variables and Finding Outliers
Module 3: Logistic Regression
Module 4: Logistic Regression Variants

Syllabus

Verified Learners can earn a certificate for this course by scoring at least 80% overall. Your score in this course is comprised of two main components: the Module Quizzes and a Summative Assessment at the end of the course.

Module Quizzes: These quizzes come at the end of each of the four modules of this course. They are comprised of 5-10 multiple choice, multiple select, fill-in-the-blank, dropdown, and numeric response questions and assess your knowledge of the preceding module -- 60% (15% for each quiz)
Summative Assessment: A final quiz that will be taken at the end of the course. It is comprised of multiple choice and multiple select questions from all four modules of the course. This activity assesses your completion of the course learning objectives -- 40%