Abstract
The measure of central tendency is the most commonly used tool in statistical data analysis. The ability to determine an ``average'' provides a way to locate data centrality. Central tendency is usually determined by one of three methods. One can calculate the mean, median or midrange of a sample set. However, does the best method to determine the central point of a distribution vary with the types of distributions involved? In this paper we attempt to determine which methods are best used for several different distributions. Specifically we will examine the Normal, Uniform, and Cauchy distributions.
Author Bio
I am currently a senior mathematics major at Tennessee Technological University and completed this paper in spring of 2001 under Dr. Michael Allen.This paper was completed during an independent project course that studied various methods and uses of the Monte Carlo Simulation. The paper was presented at Tennessee Tech's Statistics Seminar Series and published by the university asa technical report. I will be taking a break from school for the next two semesters to take a co-operative education position at Naval Surface Warfare Center, Dahlgren, VA, as a statistician student trainee. I will then return to Tennessee Tech to complete my B.S. in Mathematics with a minor inBusiness. My mathematical interests include Monte Carlo simulations and environmental statistics. I also enjoy cooking, reading books about history and watching stock car races.
Recommended Citation
McCreary, Jamie
(2001)
"Comparison of Centrality Estimators for Several Distributions,"
Rose-Hulman Undergraduate Mathematics Journal: Vol. 2:
Iss.
2, Article 1.
Available at:
https://scholar.rose-hulman.edu/rhumj/vol2/iss2/1
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