Nonparametric Statistics Course
Gain skills in nonparametric statistics for tough, skewed, and zero-filled data. Master reliable tests, effect measures, bootstrapping, and repeatable R/Python methods to produce trustworthy outcomes and simple reports for real-life studies. This course equips you to handle clinical data issues with confidence.

from 4 to 360h flexible workload
valid certificate in your country
What will I learn?
Learn key nonparametric techniques for uneven, zero-rich, and limited health results in this practical course. Cover sturdy estimators, rank tests, quantile regression, group methods, and useful effect measures. Practice data review, checks, bootstraps, permutation tests, and clear reporting for everyday health data problems.
Elevify advantages
Develop skills
- Apply strong nonparametric tests like Wilcoxon, Kruskal-Wallis, and Dunn.
- Set up bootstrap and permutation tests for skewed and zero-heavy health data.
- Calculate reliable effect sizes such as Hodges-Lehmann, Cliff’s delta, and rank-biserial r.
- Develop quantile and rank-based regression with category variables.
- Create repeatable R/Python reports with strong tables, graphs, 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.What our students say
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