Date of Award
8-1959
Document Type
Thesis
Degree Name
Master of Science
Degree Discipline
Mathematics
Abstract
Since histograms give little quantitative information about distribution, more detail descriptions are desirable. These descriptions are attained by moments of distribution. We will be primarily concerned with the first two moments. The first two moments are associated with the mean and standard deviation of a given distribution. It is to be observed now that the methods used for obtaining the mean and standard deviation of ordinary statistical data will not suffice when applied to known theoretical distributions.
Our purpose here is to consider particular theoretical freqiency distributions as models for empirical distribution.
Chapter one describes essential terminology and definitions used throughout the paper.
Chapter two discusses moments and the moment generating function. It also shows how the moment generating function actually produces moments.
Chapter three is devoted to the application of the moment generating function to the binomial distribution. It also shows that the definitions and the moment generating function produce the same moments.
Chapter four discusses the application of the moment generating function to the Poisson distribution.
Chapter five demonstrates the application of the moment generating function to the normal distribution.
Chapter six shows the application of the moment generating function to the chi-square distributions.
Finally the summary and bibliography are given.
Committee Chair/Advisor
A. D. Steward
Publisher
Prairie View A&M College
Rights
© 2021 Prairie View A & M University
This work is licensed under a Creative Commons Attribution-NonCommercial 4.0 International License.
Date of Digitization
11-2-2021
Contributing Institution
John B Coleman Library
City of Publication
Prairie View
MIME Type
Application/PDF
Recommended Citation
McAfee, O. W. (1959). Application of the Moment Generating Function to Various Other Frequency Functions. Retrieved from https://digitalcommons.pvamu.edu/pvamu-theses/659