Correlation Coefficient Goodness-of-Fit Test for the Extreme-Value Distribution

An important part of exploratory data analysis is to determine if the data at hand reasonably satisfy the assumptions underlying the statistical test to be performed. Parametric tests include assumptions about the distribution of the data, which are explored using goodness-of-fit tests. One of the e...

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Bibliographic Details
Published in:The American statistician 1989-05, Vol.43 (2), p.98-100
Main Author: Kinnison, Robert
Format: Article
Language:English
Subjects:
Correlation coefficients
Correlations
Critical values
Exact sciences and technology
Goodness of fit
Mathematics
Maximum likelihood estimation
Parametric inference
Probabilities
Probability and statistics
Proportions
Sample size
Sampling distributions
Sciences and techniques of general use
Statistics
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Summary:An important part of exploratory data analysis is to determine if the data at hand reasonably satisfy the assumptions underlying the statistical test to be performed. Parametric tests include assumptions about the distribution of the data, which are explored using goodness-of-fit tests. One of the easiest goodness-of-fit tests to use is the "correlation coefficient test." This test requires special tables that are currently readily available only for testing for fit to the Normal distribution. This article presents tables for the Type 1 (Gumbel) extreme-value distribution.
ISSN:0003-1305
1537-2731
DOI:10.1080/00031305.1989.10475627