The normality assumption is at the core of a majority of standard statistical procedures, and it is important to be able to test this assumption. In addition, showing that a sample does not come from a normally distributed population is sometimes of importance per se. Among the many procedures used to test this assumption, one of the most well-known is a modification of the Kolomogorov-Smirnov ...

The importance of normal distribution is undeniable since it is an underlying assumption of many statistical procedures such as t-tests, linear regression analysis, discriminant analysis and Analysis of Variance (ANOVA). When the normality assumption is violated, interpretation and inferences may not be reliable or valid. The three common procedures in assessing whether a random sample of indep...

Statistical analyses of the relationship between visible and near-infrared (VNIR) spectra and soil parameters usually require the normal distribution of wavelength variables. Most previous studies examined only the distribution of soil parameters, while the distribution of each VNIR spectra wavelength was ignored. Moreover, how the sample preparation process and spectral pre-processing procedur...

evapotranspiration is one of the most important components of the hydrological cycle which is directly influenced by atmospheric conditions. this study investigated annual and seasonal trends in reference evapotranspiration (et0) and its key influencing climatic variables during 1966-2005 at 10 stations in southern iran (with centrality of fars province). first, multivariate regression analysis...

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 ...

Maria E. Calzada and Stephen M. Scariano Loyola University New Orleans New Orleans, LA 70118 [email protected] Abstract: A host of materials in an introductory level statistics course relies on the “normality assumption.” However, assessing normality is a very subtle and difficult task, even for expert data analysts. To aid our student’s understanding we have written a program that implements a...

In this study, to power comparison test, different univariate normality testing procedures are compared by using new algorithm. Different and multivariate test also analyzed here. And review efficient algorithm for calculating the size corrected of which can be used compare efficiency test. Also randomness generated random numbers. For purpose, 1000 data sets with combinations sample n = 10, 20...

Glycated hemoglobin (HbA1c) is used to assess glycemic control in Type 1 diabetes (DM1) patients. Apolipoproteins play an essential role DM1 pathophysiology and may be associated with complications HbA1c. This cross-sectional observational study of 81 children adolescents both sexes diagnosed investigated the relationship between body fat distribution lean mass HbA1C apolipoprotein values, anal...