Nonparametric Statistics for Experiments

23 de octubre de 2012   | Vistas: 48 |   Experimental Economics

Daniel Houser, a researcher on experimental statistics and methods, provides along his lecture, details on nonparametric tests and their significance and application in social and economic analysis.

He shares an explanation on nonparametric tests, also known as "distribution-free tests," which are statistics that do not rely on the data belonging to any particular distribution, and also discusses the special features of these techniques. The conference is divided in two parts, the first being the Standard Nonparametric Tests and the second, Adaptive Procedures for Nonparametric tests.

Houser gives an overview of the most important statistical hypothesis tests and a comparison between one another in sample tests. For each, an explanation on how to interpret the results is presented, as well as the best scenario for the test to be applied, being among them the Wilcoxon-Mann-Whitney test, Median test, Wilcoxon signed-rank test, Jonckheere-Terpstra test, Page test, Gastwirth's modified test. He concludes by giving recommendations for analysis of binary data tests.


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Universidad Francisco Marroquín