Transcript
  • 00:01    |    
    Initial credits
  • 00:06    |    
    Introduction
  • 01:17    |    
    Standard nonparametric tests
    • Abnormal distribution in tests
    • More flexibility in tests
  • 04:22    |    
    Nonparametric tests
  • 05:40    |    
    Paired and unpaired comparison
  • 06:45    |    
    Wilcoxon-Mann-Whitney test
    • History of the test
    • Key assumptions required
    • Conditions in which assumptions are violated
    • Independent variables
    • Test statistic
  • 16:40    |    
    Example of a Wilcoxon-Mann-Whitney test (Uri Gneezy and John A. List, 2006)
    • Interpretation of the independent observations
    • Simplicity of statistics
    • Comparison between treatments
    • Scenario of one treatment consistently higher than the other
    • Scenario of treatments consistently the same
    • Distribution of Wilcoxon-Mann-Whitney test statistics
    • Asymptotic properties of Wilcoxon-Mann-Whitney test
  • 30:44    |    
    Nature of asymptotic distribution
  • 32:01    |    
    Nonparametric test and the data needed
  • 34:19    |    
    Median test
    • Degrees of freedom
    • Pros and cons of Median test
  • 39:20    |    
    Wilcoxon signed-rank test
    • Example of a Wilcoxon signed-rank test
    • Interpretation of the results of the example test
    • Asymptotic properties of Wilcoxon signed-rank test
  • 45:58    |    
    Jonckheere-Terpstra test
  • One-sided test statistic
  • 48:53    |    
    Page test
  • 49:22    |    
    Adaptive procedures for nonparametric tests
  • 50:20    |    
    Most powerful rank test
  • 53:15    |    
    Cons of the most powerful rank test
  • 54:56    |    
    Correct use of the data
  • 57:34    |    
    Gastwirth's modified rank test
  • 58:38    |    
    Differences between uniform distributions
  • 59:20    |    
    Symmetric and skewed distribution
  • 01:01:36    |    
    Adaptive distribution-free procedure
  • 01:02:03    |    
    Hogg, Fisher and Randles' (HFR) skewness and tailweight
    • Model selection scheme
    • Choice of modified tests
  • 01:05:58    |    
    Optimized algorithm 1: Model selection scheme
  • Optimization of the cup points
  • 01:09:02    |    
    Optimized algorithm 2: Choice of modified tests
  • 01:09:31    |    
    Monte-Carlo analysis of power and size
  • 01:10:49    |    
    Comparison between HH, MWW and t-test
    • Results of the t-test
    • Importance of statistical significance
  • 01:15:04    |    
    Light-tailed and right-skewed sample test
  • 01:16:38    |    
    Medium and heavy-tailed sample test
  • 01:17:30    |    
    Empirical size and power
  • 01:18:30    |    
    Adaptive procedures
  • 01:18:52    |    
    When to use adaptive procedures
  • 01:19:54    |    
    Recommendations for binary data
  • 01:22:10    |    
    Final credits


Nonparametric Statistics for Experiments

New Media  | 23 de octubre de 2012  | Vistas: 61

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.




Conferencista

Daniel Houser is chairman of the Department of Economics and director…

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