Course Information
Biostatistical Analysis using R programming provides a comprehensive training in biostatistics with hands-on training using R software. Students will learn essential statistical concepts and methods used in health science and medical research. The course also provides foundational programming skills in R, enabling students to write scripts, manage datasets, and perform statistical analyses. Through real-world examples and datasets, the course covers descriptive and inferential statistics, regression models, and survival analysis. Emphasis is placed on the interpretation of results and application of statistical techniques in health-related research.
What You Will Learn
By the end of the course, students will be able to:
- Understand and apply basic statistical concepts in health and medical research
- Use R to perform data analysis and visualize data
- Conduct hypothesis tests and interpret p-values and confidence intervals
- Calculate and interpret effect sizes such as risk ratios and odds ratios
- Apply appropriate parametric and non-parametric tests
- Conduct and interpret linear and logistic regression analyses
- Perform survival analysis and interpret Kaplan-Meier curves and hazard ratios
- Develop foundational programming skills in R for data analysis and reproducible research
Who This Course Is For
Healthcare professionals
Requirements
Basic knowledge in health sciences is required. No prior experience with R or prior training in statistics is necessary.
About the Instructor
This course is instructed by Mohammad Ali Omrani.
Course Structure
- Session 01: Introduction to biostatistics and R
Session 02: Describing data
Session 03: Probability
Session 04: Probability Distribution
Session 05: Statistical inference and hypothesis testing (comparing two means)
Session 06: Inferences for proportion
Session 07: Effect sizes (Risk ratio, Odds ratio)
Session 08: Non-parametric tests
Session 09: ANOVA
Session 10: Linear regression
Session 11: Logistic regression
Session 12: Survival analysis
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