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Nonparametric Statistics Course

Nonparametric Statistics Course
from 4 to 360h flexible workload
valid certificate in your country

What will I learn?

Acquire expertise in modern nonparametric methods tailored for skewed, zero-heavy, and censored clinical outcomes through this intensive, practical course. Explore robust estimators, rank-based tests, quantile and robust regression, cluster-aware methods, and practical effect sizes. Engage in hands-on exploratory data analysis, sensitivity checks, bootstrapping, permutation tests, and reproducible reporting designed for real-world clinical data issues.

Elevify advantages

Develop skills

  • Apply robust nonparametric tests like Wilcoxon, Kruskal-Wallis, and Dunn.
  • Design bootstrap and permutation analyses for skewed, zero-heavy clinical data.
  • Compute robust effect sizes such as Hodges-Lehmann, Cliff’s delta, and rank-biserial r.
  • Build quantile and rank-based regression models with categorical covariates.
  • Produce reproducible R/Python reports with robust tables, plots, and code.

Suggested summary

Before starting, you can change the chapters and workload. Choose which chapter to start with. Add or remove chapters. Increase or decrease the course workload.
Workload: between 4 and 360 hours

What our students say

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Very great course. Lots of rich information.
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