A Study on Teaching Method of Two-Sample Test for Population Mean Difference

두 모집단 모평균 비교의 지도에 관한 연구

  • Kim Yong-Tae (Division of information and Computer Science, Dankook University) ;
  • Lee Jang-Taek (Division of information and Computer Science, Dankook University)
  • Published : 2006.05.01

Abstract

The main purpose of this study is to investigate the effect of departures from normality and equal variance on the two-sample test when the variances are unknown. We have found that type I error brought about a little bit change which is ignorable in relation to kurtosis. But the change of type I error was mainly based on the skewness of the parent population. In introductory statistics classes where data analysis includes techniques for detecting skewness of two populations, we recommend the two-sample t-test when maximal skewness of two populations is smalter than the value 4 when the variances seem equal. Furthermore, our simulations reveal that the two-sample t-test appears somewhat more robust than that of z-test if the assumption of equal variance is satisfied. In the case of unequal variance, the two-sample t-test appears somewhat more robust provided the t-statistic using Satterthwaite's approximate degrees of freedom.