edX
edXLinear Relationship Data in Healthcare
26 studentsINTERMEDIATEEnglish
Korshub's take
Statistical methods for healthcare data, hands-on in R
Healthcare data tells stories, but only if you ask it the right questions. This intermediate course teaches you to work with the linear relationships that dominate healthcare analysis: correlation, regression, and their multivariate cousins. Each module builds on the previous one, so you move from simple questions (is there a relationship?) through more complex ones (what's the relationship after adjusting for other factors?). You'll implement methods in R and understand the assumptions that make them valid.
Essential for health data analysts, researchers, and clinical professionals who need to extract insight from healthcare datasets.
About this course
In this course, you will develop a working knowledge of linear relationship data in healthcare and practice using R statistical programming to analyze this data. You will learn about some of the most common univariate and multivariate statical methods used in healthcare data analysis and practice applying them in a statistical software package. 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: Introduction to Correlation and Linear Relationships
- Module 2: Simple OLS Linear Regression
- Module 3: Dummy Variables and Multiple OLS Linear Regression
- Module 4: OLS Linear Regression Diagnostic Tests
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