BIOSTATR
Applied Biostatistics with R
BIOSTATR
Applied Biostatistics with RFoundations
Course description
BIOSTATR is the entry point of the MHDSR pathway: a practical, rigorous introduction to applied biostatistics for health research using R. It gives participants the foundations everyone else builds on (study design, descriptive statistics, inference, regression, survival analysis, and reproducible reporting) before they move on to ML4HOR, SURV4CR, or METAR.
The course emphasizes estimation, interpretation, reproducibility, and appropriate use of statistical methods in clinical research.
Learning objectives
By the end of BIOSTATR, participants will be able to:
- formulate health research questions in statistical terms;
- identify study designs and variable types;
- organize reproducible analyses using R and Quarto;
- summarize and visualize health data appropriately;
- interpret confidence intervals, p-values, and effect estimates;
- compare groups using suitable statistical tests;
- fit and interpret linear and logistic regression models;
- understand the basics of survival analysis and diagnostic accuracy;
- recognize issues related to missing data and causal thinking;
- produce a reproducible statistical report.
Schedule
| No. | Topic |
|---|---|
| 1 | Introduction to biostatistics, study design & reproducible R/Quarto workflow |
| 2 | Descriptive statistics & data visualization |
| 3 | Estimation, statistical inference & group comparisons |
| 4 | Correlation and linear regression |
| 5 | Logistic regression and GLMs |
| 6 | Survival analysis and diagnostic accuracy |
| 7 | Missing data, causal thinking, sample size & reporting |
| 8 | Final synthesis and mini-project |
Practical information
- Audience
- Health researchers, clinicians, students with no statistics background required
- Prerequisites
- None; R/RStudio setup covered in Session 1
- Format
- Live sessions, slides, notebooks, datasets, exercises
- Schedule
- Mon/Wed/Fri 18h00–20h00, Sun 10h00–12h00 (Morocco time)
- Tools
- R, RStudio, Quarto
- Assessment
- Reproducible Quarto mini-project
- Next step
- ML4HOR, SURV4CR, or METAR