Author ORCID Identifier

https://orcid.org/0009-0009-0253-0156

Date of Award

8-7-2024

Degree Type

Thesis

Degree Name

Master of Science (MS)

Department

Mathematics and Statistics

First Advisor

Yichuan Zhao

Second Advisor

Jing Zhang

Third Advisor

Li-Hsiang Lin

Abstract

The thesis aims to determine, independent of sample size, a quick and effective way to test the equality of several samples without making any assumptions about their distribution. For example, we could use a k-sample test to compare the efficacy of various vaccines and see if they are equally effective. We created a new test by combining empirical likelihood methods with the ’divide and conquer’ strategy. Ninety-five percent of the time, our test correctly identified samples from the same distribution, and eighty percent of the time, samples from different distributions. It is similar to other tests but completed in a fraction of the time needed by current methods, producing results much faster

DOI

https://doi.org/10.57709/37442086

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