Mitchell Grant is a self-taught investor with over 5 years of experience as a financial trader. He is a financial content strategist and creative content editor. Timothy Li is a consultant, accountant ...

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 ...

In this article, we revisit some problems in non-parametric hypothesis testing. First, we extend the classical result of Bahadur & Savage [Ann. Math. Statist. 25 (1956) 1115] to other testing problems ...

Scandinavian Journal of Statistics, Vol. 28, No. 4 (Dec., 2001), pp. 725-732 (8 pages) We consider the comparison of point processes in a discrete observation situation in which each subject is ...

Linear models, generalized linear models, and nonlinear models are examples of parametric regression models because we know the function that describes the relationship between the response and ...

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 ...

Explain why and when a non-parametric test should be used or may be preferred for simple comparison over a parametric method Explain the general principles and process of performing a non-parametric ...

Understanding some statistics is important for general science literacy. Below are some common statistics resources that may be useful for your project work. To support your professional development, ...

Download PDF More Formats on IMF eLibrary Order a Print Copy Create Citation The purpose of this paper is to compare in-sample and out-of-sample performances of three parametric and non-parametric ...