Award Date

1-1-2003

Degree Type

Thesis

Degree Name

Master of Science (MS)

Department

Mathematical Sciences

First Committee Member

Ashok K. Singh

Number of Pages

60

Abstract

In this thesis we will develop a method for the construction of a non-parametric confidence interval and compare it to parametric confidence intervals for the mean of a population distribution. Using Monte Carlo simulation, we will examine the performance of both confidence intervals on data from different types of distributions. In particular, we are interested in examining how these confidence intervals perform when the data is known to come from a skewed distribution. Our goal is to illustrate the superiority of our new method against a traditional parametric approach for estimating parameters, particularly on skewed data.

Keywords

Confidence; Data; Evaluation; Intervals; Parametric; Performance; Skewed

Controlled Subject

Statistics

File Format

pdf

File Size

1699.84 KB

Degree Grantor

University of Nevada, Las Vegas

Language

English

Permissions

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Identifier

https://doi.org/10.25669/dxxn-3muc


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