BACKGROUND Student's two-sample t test is generally used for comparing the means of two independent samples, for example, two treatment arms. Under the null hypothesis, the t test assumes that the two samples arise from the same normally distributed population with unknown variance. Adequate control of the Type I error requires that the normality assumption holds, which is often examined by mea...

The classification of twin pairs based on zygosity into monozygotic (MZ) or dizygotic (DZ) twins is the basis of most twin analyses. When zygosity information is unavailable, a normal finite mixture distribution (mixture distribution) model can be used to estimate components of variation for continuous traits. The main assumption of this model is that the observed phenotypes on a twin pair are ...

The objective of this study is to evaluate the performance PT Angkasa Pura II using balanced scorecard methodology. According Slovin formula, there were 98 employees in sample size. essential data included was gathered by distributing questionnaires all participants. SPSS version 23 software for Windows operating system facilitates use multiple regression as analysis technique study. Furthermor...

Consider testing normality against a one-parameter family of univariate distributions containing the normal distribution as the boundary, e.g., the family of t-distributions or an infinitely divisible family with finite variance. We prove that under mild regularity conditions, the sample skewness is the locally best invariant (LBI) test of normality against a wide class of asymmetric families a...

This study aims to determine the effect of diversification strategy, good corporate governance implementation on firm value. The consisted 41 companies were classified as withthe most trusted category in Indonesia 2015 by SWA magazine. analysis technique used is multiple regression and testing using SPSS for Windows version 22 also test classical assumption normality test, autocorrelation multi...

In this paper we test the mean variance efficiency of the benchmark portfolio in the absence of a risk-free rate. We propose exact likelihood-based bound mean-variance efficiency tests of the market portfolio, allowing for a wide class of elliptical error distributions. Our tests are developed using multivariate linear regressions (MLR). It is well known that despite their simple statistical st...

In this paper we test the mean variance efficiency of the benchmark portfolio in the absence of a riskfree rate. We propose likelihood-based exact bound mean-variance efficiency tests of the market portfolio, allowing for a wide class of elliptical error distributions. Our tests are developed using multivariate linear regressions (MLR). It is well known that despite their simple statistical str...

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...

Consider testing normality against a one-parameter family of univariate distributions containing the normal distribution as the boundary, e.g., the family of t-distributions or an infinitely divisible family with finite variance. We prove that under mild regularity conditions, the sample skewness is the locally best invariant (LBI) test of normality against a wide class of asymmetric families a...