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Non-Parametric Statistics: Home

Non-parametric methods are used to make inferences about infinite dimensional parameters in statistical models.


A survey of statistical methods that do not rely on parametric assumptions. Knowledge of introductory statistics at this level  is assumed; this course is in some ways a sequel. As such, it will review the parametric techniques learned in that and similar introductory courses, and compare them to nonparametric alternatives to see when one technique outperforms another.

The three major sections of the course are: Classical nonparametric statistics: One-, two-, and k-sample methods, including methods based on the binomial, on ranks, and on scores.



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