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 ...

Asymptotic lower bounds for estimation of the parameters of models with both parametric and nonparametric components are given in the form of representation theorems (for regular estimates) and ...

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 ...

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

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 ...

An introduction to analysing quantitative data including topics such as, understanding the distribution of data variables, and parametric and non-parametric statistical tests. Data refers to numbers, ...

What is the Kruskal–Wallis test? The Kruskal–Wallis test is a statistical test used to compare two or more groups for a continuous or discrete variable. It is a non-parametric test, meaning that it ...

This example continues to examine the effects of a change in the cost of crude and the selling price of jet fuel. Suppose that you know the cost of ARABIAN_LIGHT crude is likely to increase 30 units, ...

Statistical testing in Python offers a way to make sure your data is meaningful. It only takes a second to validate your data ...