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MATH-493: Applied biostatistics

Summary

This course covers topics in applied biostatistics, with an emphasis on practical aspects of data analysis using R statistical software. Topics include types of studies and their design and analysis, high dimensional data analysis (genetic/genomic) and other topics as time and interest permit.

Lectures

Instructors

Official source

https://edu.epfl.ch/coursebook/en/applied-biostatistics-MATH-493

Moodle Page

http://go.epfl.ch/MATH-493

About this result

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Summary

Lectures

Instructors

Official source

https://edu.epfl.ch/coursebook/en/applied-biostatistics-MATH-493

Moodle Page

http://go.epfl.ch/MATH-493

About this result

Ontological neighbourhood

Statistics

Data analysis: Regression analysis

Statistical inference: Statistical hypothesis testing

Lectures in this course (17)

Reproducible Research: Principles and Tools

Covers the principles and tools for reproducible research in biostatistics, emphasizing the importance of complete documentation and the use of text editors for compiling source documents.

Bivariate Data Analysis: Correlation and Regression

Explores bivariate data analysis, correlation, and regression techniques for model assessment.

Survival Analysis: Modeling and Estimation

Covers survival data analysis, Cox regression, Kaplan-Meier estimator, and log-rank test.

Survival Analysis: Cox Proportional Hazards Model

Introduces the Cox proportional hazards model for survival analysis, covering estimation, assessment of assumptions, and interpretation using residuals.

Categorical Data Analysis: Methods and Examples

Explores the analysis of categorical and discrete data with examples.

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