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Nonparametric Statistics Course

Nonparametric Statistics Course
from 4 to 360h 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. Explore robust estimators, rank tests, quantile regression, cluster methods, and effect measures. Apply exploratory data analysis, sensitivity analysis, bootstrapping, permutation testing, and reproducible reporting for real clinical challenges.

Elevify advantages

Develop skills

  • Apply robust nonparametric tests including Wilcoxon, Kruskal-Wallis, and Dunn procedures.
  • Design bootstrap and permutation tests tailored for skewed and zero-heavy clinical datasets.
  • Calculate reliable effect sizes such as Hodges-Lehmann, Cliff’s delta, and rank-biserial correlation.
  • Develop quantile and rank-based regression models incorporating categorical variables.
  • Generate reproducible reports in R or Python featuring robust tables, visualisations, 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.
Workload: between 4 and 360 hours

What our students say

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Great course. A lot of valuable information.
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