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Nonparametric Statistics Course

Nonparametric Statistics Course
flexible workload of 4 to 360h
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. You will explore robust estimators, rank tests, quantile regression, cluster methods, and effect measures, while applying EDA, bootstrapping, permutation tests, and reproducible workflows suited to everyday clinical data issues.

Elevify advantages

Develop skills

  • Apply strong nonparametric tests like Wilcoxon, Kruskal-Wallis, and Dunn.
  • Set up bootstrap and permutation tests for skewed clinical data with lots of zeros.
  • Calculate reliable effect sizes such as Hodges-Lehmann, Cliff’s delta, and rank-biserial r.
  • Develop quantile and rank regression models including category variables.
  • Create reproducible R/Python reports featuring robust tables, graphs, and scripts.

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

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