A New Test for correlation on Bivariate Non-Normal Distribution
College of Arts and Sciences
Master of Science in Mathematical Sciences (MS)
Mathematics & Statistics
The sampling distribution of the sample correlation coefficient is unstable, even when the population is bivariate normally distributed. It is the main reason why a reasonably good test for the correlation is difficult to obtain, not to mention that most of the populations in the real world are not normally distributed. This thesis proposes a new method to conduct a right-tailed test for the correlation on bivariate non-normal distributions. The test unitizes the inverse Edgeworth expansion on the standardized form of the sample correlation. A comparative simulation study shows that the new test controls the type I error rates very well for all the distributions considered. An investigation of the power performance of the new test is also provided.
Wang, Ping, "A New Test for correlation on Bivariate Non-Normal Distribution" (2009). UNF Graduate Theses and Dissertations. 1054.