Nonparametric Statistics Course
This course equips you with essential nonparametric statistics skills for analysing complex, skewed, and zero-heavy clinical data. Delve into robust tests, effect sizes, bootstrapping, permutation methods, and reproducible R/Python workflows to produce dependable results and professional reports suited to rigorous real-world research demands.

4 to 360 hours of flexible workload
certificate valid in your country
What Will I Learn?
Gain expertise in nonparametric techniques for handling skewed, zero-inflated, and censored data in clinical settings through this practical course. You will explore robust estimators, rank tests, quantile regression, cluster methods, and effect sizes, while applying EDA, bootstrapping, permutation tests, and reproducible reporting for real clinical challenges.
Elevify Advantages
Develop Skills
- Apply robust nonparametric tests including Wilcoxon, Kruskal-Wallis, and Dunn tests.
- Design bootstrap and permutation analyses tailored for skewed and zero-heavy clinical data.
- Calculate robust effect sizes such as Hodges-Lehmann, Cliff’s delta, and rank-biserial r.
- Develop quantile and rank-based regression models incorporating categorical covariates.
- Generate reproducible R/Python reports featuring robust tables, plots, and code.
Suggested Summary
Before starting, you can change the chapters and the workload. Choose which chapter to start with. Add or remove chapters. Increase or decrease the course workload.What our students say
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