many commonly used statistical methods require that the population distribution be nearly normal. unfortunately, in some papers the one-sample kolmogorov-smirnov test has been used for testing normality while the assumptions of applying this test are not satisfied. to conduct this test, it is assumed that the population distribution is fully specified. in practical situation where the mean and ...

The multivariate normality of stock returns is a crucial assumption in many tests of assets pricing models. While past Australian research has examined the univariate normality of returns, univariate test statistics are unreliable for testing multivariate normality since they ignore the contemporaneous correlation between asset returns. This paper utilises a multivariate test procedure, based o...

Functional mapping has been a powerful tool in mapping quantitative trait loci (QTL) underlying dynamic traits of agricultural or biomedical interest. In functional mapping, multivariate normality is often assumed for the underlying data distribution, partially due to the ease of parameter estimation. The normality assumption however could be easily violated in real applications due to various ...

statistical errors are common in scientific literature and about 50% of the published articles have at least one error. the assumption of normality needs to be checked for many statistical procedures, namely parametric tests, because their validity depends on it. the aim of this commentary is to overview checking for normality in statistical analysis using spss.

This article analyzes whether the existing tests for the p× p covariance matrix Σ of the N independent identically distributed observation vectors with N ≤ p work under non-normality. We focus on three hypotheses testing problems: (1) testing for sphericity, that is, the covariance matrix Σ is proportional to an identity matrix Ip; (2) the covariance matrix Σ is an identity matrix Ip; and (3) t...

The article is devoted to normality assumption in statistical data analysis. It gives a short historical review of the development of scientific views on the normal law and its applications. It also briefly covers normality tests and analyzes possible consequences of using the normality assumption incorrectly.

There are many new methods for solving constraint satisfaction problems proposed in recent years. Due to their complexity, a theoretical analysis on their average-case behaviours seems to be very difficult. Researchers tend to adopt an empirical approach to evaluate constraint satisfaction techniques. When empirical results are ready, statistical techniques are often employed for analysis. The ...