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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?

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 sizes. Apply EDA, bootstrapping, permutation tests, and reproducible workflows suited to clinical data realities.

Elevify advantages

Develop skills

  • Apply key nonparametric tests like Wilcoxon, Kruskal-Wallis, and Dunn procedures.
  • Conduct bootstrap and permutation tests for skewed clinical datasets.
  • Calculate robust effect sizes including Hodges-Lehmann and Cliff’s delta.
  • Develop quantile and rank regression models using categorical factors.
  • Generate reproducible reports in R or Python with tables, visuals, 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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