Award Date

1-1-2005

Degree Type

Thesis

Degree Name

Master of Science (MS)

Department

Mathematical Sciences

First Committee Member

Ashok K. Singh

Number of Pages

48

Abstract

A geometric random variable models the number of trials required to obtain the fist success in a Bernoulli process. This distribution has been used by Merrill (2005) as a probability model for the distribution of drivers yielding to pedestrians in a traffic microsimulation investigation. The sample proportion of yielding drivers was calculated using the method of moments, and the bootstrap method was used for computing a confidence interval (CI) for the success probability. The properties of this CI for the geometric distribution, however, have not been investigated. The main objective of this thesis is to develop the performance of the bootstrap method, and then propose a Bayesian analysis for estimating a confidence interval for the population proportion when the data follow a geometric distribution.

Keywords

Confidence; Distribution; Estimation; Geometric; Interval

Controlled Subject

Statistics

File Format

pdf

File Size

1105.92 KB

Degree Grantor

University of Nevada, Las Vegas

Language

English

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