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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 measures. Apply exploratory data analysis, sensitivity analysis, bootstrapping, permutation testing, and reproducible workflows suited to clinical data realities.

Elevify advantages

Develop skills

  • Apply key nonparametric tests including Wilcoxon, Kruskal-Wallis, and Dunn procedures.
  • Develop bootstrap and permutation strategies tailored for skewed and zero-heavy clinical datasets.
  • Calculate reliable effect sizes such as Hodges-Lehmann, Cliff’s delta, and rank-biserial r.
  • Construct quantile and rank-based regression models incorporating categorical variables.
  • Generate reproducible reports in R or Python featuring robust tables, graphics, and scripts.

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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