Testing For Normality

By H. Thode. 2002

481 citations recorded by the source corpus.

View Paper: https://www.semanticscholar.org/paper/3bd717c075135e9ef855a1d5b9eb52a0587cc0ff

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In Statistics and Probability

Citations in the corpus

Unraveling the diverse nature of service quality in a sharing economy: A social exchange theory perspective of Airbnb accommodation (2017, unknown): “The results provided in Appendix B show that univariate normality of the dataset should not be considered as an issue, since both skewness and kurtosis were within acceptable limits for all indicators as proposed in the literature (Thode, 2002).”
Quotient correlation: A sample based alternative to Pearson’s correlation (2008, methodology): “These procedures are summarized in books by Cromwell, Labys and Terraza (1994), Cromwell, Hannan, Labys and Terraza (1994), Kanji (1999) and Thode (2002), among others.”
Normalization of the Kolmogorov–Smirnov and Shapiro–Wilk tests of normality (2015, background): “A review of techniques for solving such problems can be found, for example, in Thode (2002).”
An introduction to sampling via measure transport (2016, methodology): “t is only approximate, then the pushforward samples will not have independent and standard normal components, and one can quantify their deviation from such normality using standard statistical tests [86]. 4.3 Computing the inverse map Up to now, we have shown how to compute the triangular inverse t”
Lambert W random variables—a new family of generalized skewed distributions with applications to risk estimation (2009, methodology): “For Gaussian input various tests are available [Jarque–Bera, Shapiro–Wilk, among others; see Thode (2002)], for other distributions a Kolmogorov–Smirnov test can be used.6 5.2.1.”
Variations of Q–Q Plots: The Power of Our Eyes! (2015, background): “In so-called de-trended Q-Q plots (Thode, 2002, p. 25–26) the y axis is changed to show the difference between theoretical and sample quantiles.”
Normalization of Shapiro-Wilk test with known mean (2014, background): “In literature, this test is recommended as very powerful (Thode, 2002; Razali and Wah, 2011) for the null hypothesis that a random variable X is normally distributed with unknown parameters.”