"Some Modified Test Statistics for Testing the Population Signal to Noi" by Samantha Menendez
 

Document Type

Thesis

Degree

Master of Science (MS)

Major/Program

Statistics

First Advisor's Name

B.M. Golam Kibria

First Advisor's Committee Title

Committee chair

Second Advisor's Name

Florence George

Second Advisor's Committee Title

Co-Committee Chair

Third Advisor's Name

Sneh Gulati

Third Advisor's Committee Title

Committee member

Keywords

Signal to Noise, Signal, Noise, Signal to Noise Ratio, Ratio

Date of Defense

6-16-2023

Abstract

SNR is a measure of the strength of desired data relative to undesigned data. Population SNR is equal to the population mean divided by the population standard deviation. In practice, commonly in image processing, a high SNR means that the signal strength is stronger in relation to the noise. Having higher SNR provides more useful information. This thesis considers fifteen existing and proposed test statistics for testing the population SNR. A theoretical comparison among the test statistics is not possible, a Monte Carlo simulation study has been conducted. The performance of the test statistics is based on the empirical size and power of the tests considering a significance level 0.05. The simulation study resulted that some existing and proposed methods are performing well in some conditions. However, Method 10 performed the best in all simulation conditions. Three real life data are analyzed to illustrate the performance of the test statistics.

Identifier

FIDC011218

Share

COinS
 

Rights Statement

Rights Statement

In Copyright. URI: http://rightsstatements.org/vocab/InC/1.0/
This Item is protected by copyright and/or related rights. You are free to use this Item in any way that is permitted by the copyright and related rights legislation that applies to your use. For other uses you need to obtain permission from the rights-holder(s).