Is Walmart Safe?

1996 WordsNov 13, 20128 Pages
Is Walmart Safe? The Effects of Established Supercenter Walmarts to Property Crime Rates within Dekalb and Gwinnett County from 1999-2010 Class: Economics & Finance Modeling Professor: Doctor Derek Tittle Dream Team Group Members: Alexandra E Steingaszner Brian-Paul Gude Kristopher Bryant Norman Gyamfi Samantha Gowdy | Disclaimer This report has been created in the framework of a student group project and the Georgia Institute of Technology does not officially sanction its content. Executive Summary Every year, Walmart is accused of increasing crime in areas within which it builds Walmart Supercenters. Yet, research and data analyses largely disprove these claims, as they reveal that other factors such as…show more content…
Iterations of analysis eliminated data points that were listed as “unusual observations,” or any data point with a large standardized residual. After 5 iterations, the analysis showed improved residual plots. Randomness in the versus fits and versus order plots means that the linear regression model is appropriate for the data; a straight line in the normal probability plot illustrates the linearity of the data, and a bell shaped curve in the histogram illustrates the normality of the data. Because of the method of monthly data collection, absolute randomness could not be obtained; however, it was decided that 5 iterations was sufficient because the sixth iteration showed a decrease in the quality of the residual plots. The first test performed was the p-value test of the individual variables. A p-value is the probability, ranging from 0 to 1, of obtaining a test statistic similar to the one that was actually observed. The only input that did not have a p-value less than 0.05, which was the chosen significance level, was the “Number of Walmarts” variable; the number of Walmarts has no specific effect on the output, property crime rate. The R2 of the analysis, or the coefficient of determination, provides a measure of how well future outcomes are likely to be predicted by the model. R2 values range from 0 to 100% (or 0 and 1) and the
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