ANALYSING REGIONAL EXPORT DATA BY THE MODIFIED GENERALIZED F-TEST

Classical F-test is used for testing equality of more than two group means under normality and variance homogeneity. Classical F test is most powerful parametric method among the parametric statistical methods in case of the assumptions are hold. However, the assumptions are not always satisfied in real life. Thus researchers study on improving methods to solve this problem. Welch, Generalized F, Parametric Bootsrap tests are proposed for testing equality of group means under variance heterogeneity. These methods just give better results under variance heterogeneity but they are not same in case of violation of normality assumption due to researches. In this article, modified generalized F-test is considered which is proposed for variance heterogeneity and non-normality caused by outlier. To show the efficiency of this method, testing equality of annual export amounts of geographical regions under variance heterogeneity and non-normality caused by outlier. As a result, it is stated that significant differences between regions are detected only by modified generalized F-test