Statistics with R for Healthcare Research

Develop the statistical knowledge and R programming skills needed to analyse healthcare and research data confidently. This course introduces healthcare professionals to statistical concepts alongside practical implementation in R using realistic clinical and public health datasets.

Ideal for healthcare researchers, postgraduate students and anyone involved in evidence-based healthcare.

Learning Outcomes

By the end of this course you will be able to:

• Understand core statistical concepts.
• Import and manage healthcare datasets in R.
• Perform descriptive and inferential analyses.
• Create publication-quality graphs.
• Conduct hypothesis testing.
• Build regression models.
• Interpret statistical outputs confidently.

Course Modules

• Module 1: Introduction to R & RStudio
  • Install R, navigate RStudio and understand the R environment.
• Module 2: Working with Healthcare Data
  • Import, organise and manipulate datasets.
• Module 3: Descriptive Statistics
  • Summarise healthcare data using measures of central tendency and variation.
• Module 4: Data Visualisation
  • Create professional graphs using ggplot2.
• Module 5: Probability & Distributions
  • Understand probability concepts and commonly used statistical distributions.
• Module 6: Hypothesis Testing
  • Perform t-tests, chi-square tests and ANOVA.
• Module 7: Correlation & Regression
  • Analyse relationships between healthcare variables.
• Module 8: Logistic Regression
  • Model binary healthcare outcomes.
• Module 9: Healthcare Research Applications
  • Apply statistical methods to epidemiology, clinical research and public health.
• Module 10: Final Project
  • Analyse a healthcare research dataset and produce a professional statistical report.

Skills You’ll Gain

• R Programming
• RStudio
• ggplot2
• Healthcare Statistics
• Hypothesis Testing
• Regression Analysis
• Research Methods
• Epidemiology