Assessing the assumption of multivariate normality is required by many parametric multivariate statistical methods, such as MANOVA, linear discriminant analysis, principal component analysis, canonical correlation, etc. It is important to assess multivariate normality in order to proceed with such statistical methods. There are many analytical methods proposed for checking multivariate normalit...

The coffee shop business has been growing and mushrooming in the last 5 years. For this reason, various efforts are made to maintain or business. main problem studied study is how location atmosphere of warkop influence buying decision at a sane Kuningan Village, Blitar Regency. Thus, aims find out on purchasing decisions village, district, either partially simultaneously. To apply these object...

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 purpose of this study was to determine the effect inflation and return on equity (ROE) stock returns manufacturing companies in food beverage sub sector Indonesia 2014-2019. sample used is annual data from 2014 - 2019. Hypothesis testing uses panel regression analysis. population are sub-sector listed Stock Exchange period secondary with documentation method. Before analyzing data, a classi...

Generalized linear mixed models are popular to regress a discrete response when there is clustering, e.g. in longitudinal studies or in hierarchical data structures. It is standard to assume that the random effects have a normal distribution. Recently, it has been examined whether wrongly assuming a normal distribution for the random effects is important for the estimation of the fixed effects ...