edX
edXIntroduction to Healthcare Data Analysis
346 studentsBEGINNEREnglish
Korshub's take
Healthcare Statistics Through Applied Method
Rather than pure theory, this course grounds statistical methods in healthcare contexts. You'll build skills in descriptive statistics, hypothesis testing, univariate and multivariate analysis—then apply each in R with real data scenarios.
Five modules progress logically from data distribution through t-tests and ANOVA, with hands-on practice ensuring you can both understand and execute the analysis.
About this course
In this course, you will develop a solid foundational understanding of the most common statistical methods used in health care data analysis.
This course covers some of the most common univariate and multivariate statistical methods used in healthcare data analysis. Students will also learn how to apply these methods using a statistical software package. The course covers basic data wrangling that is necessary for data analysis. It uses examples from the healthcare industry. This course focuses on the use of statistical methods although there may be some discussion of the mathematical underpinnings and 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 5 modules that you should complete in order, as each subsequent module builds on the previous one.
- Module 1: Descriptive Statistics and Data Distributions
- Module 2: Sampling Distribution and Hypothesis Tests
- Module 3: Visualize and Summarize Data in R
- Module 4: Independent and Paired Sample t-tests
- Module 5: ANOVA
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