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Journal ArticleDOI

Use of the Correlation Coefficient with Normal Probability Plots

Stephen W. Looney, +1 more
- 01 Feb 1985 - 
- Vol. 39, Iss: 1, pp 75-79
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TLDR
Goodness-of-fit tests were constructed using this technique for several commonly used plotting positions for the normal distribution as discussed by the authors, which were then compared on the basis of power against certain nonnormal alternatives.
Abstract
The use of the correlation coefficient is suggested as a technique for summarizing and objectively evaluating the information contained in probability plots. Goodness-of-fit tests are constructed using this technique for several commonly used plotting positions for the normal distribution. Empirical sampling methods are used to construct the null distribution for these tests, which are then compared on the basis of power against certain nonnormal alternatives. Commonly used regression tests of fit are also included in the comparisons. The results indicate that use of the plotting position pi = (i - .375)/(n + .25) yields a competitive regression test of fit for normality.

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Citations
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A generic framework for spatial prediction of soil variables based on regression-kriging

TL;DR: In this paper, a methodological framework for spatial prediction based on regression-kriging is described and compared with ordinary kriging and plain regression, which can adopt both continuous and categorical soil variables in a semi-automated or automated manner.
Book

Applied Multivariate Analysis

TL;DR: In this article, the Multivariate Normal Distribution, Multivariate Normality, and Covariance Structure were used for one-and two-sample tests to compare the performance of vector and matrix algebra.
Book

Handbook of statistical distributions with applications

TL;DR: The StatCalc Reliability Model Fitting Methods of Estimation Inference Random Number Generation Some Special Functions and Examples are presented.
Journal ArticleDOI

Goodness‐of‐fit tests for regional generalized extreme value flood distributions

TL;DR: This paper developed critical values and formulas for computing several goodness-of-fit tests for the generalized extreme value (GEV) distribution, which can check if data available for a site are consistent with a regional GEV distribution, except for scale.
References
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Journal ArticleDOI

An Analysis of Variance Test for Normality (Complete Samples)

S. S. Shapiro, +1 more
- 01 Dec 1965 - 
TL;DR: In this article, a new statistical procedure for testing a complete sample for normality is introduced, which is obtained by dividing the square of an appropriate linear combination of the sample order statistics by the usual symmetric estimate of variance.
Book

Applied Multivariate Statistical Analysis

TL;DR: In this article, the authors present an overview of the basic concepts of multivariate analysis, including matrix algebra and random vectors, as well as a strategy for analyzing multivariate models.
Journal ArticleDOI

Applied Multivariate Statistical Analysis.

TL;DR: In this article, the authors present an overview of the basic concepts of multivariate analysis, including matrix algebra and random vectors, as well as a strategy for analyzing multivariate models.
Journal ArticleDOI

On the Kolmogorov-Smirnov Test for Normality with Mean and Variance Unknown

TL;DR: In this paper, the power of the Kolmogorov-smirnov test is investigated and a table for testing whether a set of observations is from a normal population when the mean and variance are not specified but must be estimated from the sample.