Masters Thesis, Dept. of Mathematics & Computer Science, Texas Woman's University .
ISSN/ISBN: Not available at this time. DOI: Not available at this time.
Abstract: The purpose of this study was to analyze the buyout, or "buy now," prices in auction houses of virtual environments, such as World of Warcraft and Guild Wars 2. Human players interact with an auction house user interface in order to buy or sell in-game items, purchasable with in-game currency. Players wishing to sell items can post their items on the auction house for set lengths of time, as well as set a starting bid amount and/or an amount in which other players can instantly buy the item. Since the establishment of Benford's Law, it has been supported that data generated by humans typically does not follow Benford's Law, proving to be a beneficial tool in detecting fraudulent accounting data. However, this study shows that the leading significant digits of these buyout prices in virtual environments created by humans follow Benford's Law by utilizing Kuiper's goodness of fit V_n test, a modified Kolmogorov-Smirnov test.
Bibtex:
@mastersThesis{,
AUTHOR = {Endress, Megan Brooke},
TITLE = {Benford's law and humanly generated prices in auction houses and buyout systems of virtual worlds},
SCHOOL = {Texas Woman's University },
YEAR = {2014},
URL = {https://twu-ir.tdl.org/handle/11274/3642},
}
Reference Type: Thesis
Subject Area(s): General Interest, Statistics