This short course will provide an overview of non-parametric statistical techniques. The course will first describe what non-parametric statistics are, when they should be used, and their advantages ...

The digitization of production and technological resources linked to the development of increasingly sophisticated tools has a direct impact on the contemporary practice of architecture and urbanism.

We provide novel, high-order accurate methods for non-parametric inference on quantile differences between two populations in both unconditional and conditional settings. These quantile differences ...

This paper considers the estimation of the density of an absolutely continuous distribution with respect to an unknown baseline distribution F, and the estimation of ...

Nonparametric estimation and U-statistics have emerged as vital tools in modern statistical analysis, offering robust alternatives to traditional parametric methods. Nonparametric techniques bypass ...

We have performed a genome scan using 25 nuclear families consisting of right-handed parents with at least two left-handed children. Handedness was assessed as a qualitative trait using a laterality ...

Parametric tests make assumptions that aspects of the data follow some sort of theoretical probability distribution. Non-parametric tests or distribution free methods do not, and are used when the ...

Please Note: Blog posts are not selected, edited or screened by Seeking Alpha editors. A lot of statistic analysis is based on parametric statistics. One of the most crucial assumptions is the bell ...

Statistical testing in Python offers a way to make sure your data is meaningful. It only takes a second to validate your data. Having data is only half the battle. How do you know your data actually ...