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KEDEM, BENJAMIN FOSTER, KEVIN MATTHEW Digital Repository at the University of Maryland University of Maryland (College Park, Md.) Mathematical Statistics 2009-07-02T05:56:22Z 2009-07-02T05:56:22Z 2008 http://hdl.handle.net/1903/9217 In this thesis we are going to use U.S. Census data to study median household income distribution for 13 U.S. counties and seven U.S. states. Over the years, researchers have fitted income data with various probability distributions. During our review of the literature, we saw that researchers do not agree on any one best distribution. We will be looking at lognormal, gamma and Weibull, each of which has two parameters. We will also investigate the Singh-Maddala, which has three parameters. Finally, we will introduce the Generalized Beta II, which has four parameters. These distributions will be tested using Mean Squared Error, Mean Absolute Error, Chi-square Goodness-Of-Fit, Akaike's Information Criterion and Bayesian Information Criterion. We also use the graphical technique of QQ Plots. We discover that the Singh-Maddala most often provides the best fit model for our income data, and we make the recommendation that users choose the Singh-Maddala distribution as their model when studying median household income distribution. 357051 bytes application/pdf en_US MODELING MEDIAN HOUSEHOLD INCOME DISTRIBUTION Thesis Statistics CENSUS DISTRIBUTION GAMMA INCOME LOGNORMAL SINGH-MADDALA open.access