Date of Award
Summer 8-11-2011
Degree Type
Closed Thesis
Degree Name
Master of Science (MS)
Department
Mathematics and Statistics
First Advisor
Dr.Gengsheng Qin
Abstract
The correlation coefficient (CC) is a standard measure of the linear association between two random variables. The CC plays a significant role in many quantitative researches. In a bivariate normal distribution, there are many types of interval estimation for CC, such as z-transformation and maximum likelihood estimation based methods. However, when the underlying bivariate distribution is unknown, the construction of confidence intervals for the CC is still not well-developed. In this thesis, we discuss various interval estimation methods for the CC. We propose a generalized confidence interval and three empirical likelihood-based non-parametric intervals for the CC. We also conduct extensive simulation studies to compare the new intervals with existing intervals in terms of coverage probability and interval length. Finally, two real examples are used to demonstrate the application of the proposed methods.
DOI
https://doi.org/10.57709/2101457
Recommended Citation
Jung, Aekyung, "Interval Estimation for the Correlation Coefficient." Thesis, Georgia State University, 2011.
doi: https://doi.org/10.57709/2101457