2nd choice - Gm533- Statistic Paper EXECUTIVE SUMMARY...

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Gm533- Statistic Paper EXECUTIVE SUMMARY During the 1980s there was rash of property crimes in the United States. Business executives and community leaders was taken at back. They chose to look for and find these determinants of property crimes and figure out how to remedy those issues. The task at hand was to provide evidence for or against common perceptions about property crime. Prove if crime rates are higher in urban areas or rural areas. Whether unemployment or education levels contributed to property crime rates, as well as public assistance? Lastly establish what other possible factors relate to property crimes? PCRIMES data was used to prepare a report on the characteristics of and determinants of property crimes in the United States. PCRIMES Property crime rate per hundred thousand inhabitants (property crimes include burglary, larceny, theft and motor vehicle theft); calculated as number of property crimes committed divided by total population/100,000 PINCOME Per capita income for each state DROPOUT High School Dropout rate (%, 1987) PRECIP Average precipitation in inches in the major city in each state over 1951- 1980 PUBAID Percentage of public aid recipients (1987) DENSITY Population/total square miles KIDS Public aid or families with children, dollars per family UNEMPLOY Percentage of unemployed workers URBAN Percentage of the residents living in urban areas STATE 50 States of America The task required that it show the association between crime and the different variables; such as location, income levels, education, climate, public aid, population density, family size and unemployment rates. From the studies it was recommended to use a regression analysis and established that crime is the dependent variable, and that the others were independent variables. After running a regression analysis and hypothesis testing it was concluded that high school dropout rates had a strong positive correlation with property crime rates. Public aid recipients and their families however proved to be the most responsive as there is a decrease of 113.7 % in property crime rate with increase in public aid. Surprisingly, unemployment does not contribute to property crime rate because the regression indicates that for each percentage increase in unemployed workers, we can expect a decrease of 46% in property crime rate. It can be concluded that property crime rates are certainly high in urban than rural areas because rural communities have better social bonds than in urban areas where it is easier to fence stolen goods as well as commit felony crime. INTRODUCTION Step 1. Establish the predictor and predicted. Crime is the dependent variable Formula: Y= β0 + β1X1 + β2X2 + β3X3 + β4X4 + β5X5 + β6X6 + β7X7 + β8X8 Independent Variables X1 = Pincome X2 = Dropout
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X3 = Precip X4 = Pubaid X5 = Density X6 = Kids X7 = Unemploy X8 = Urban Ho: β1…. .β8 = 0 (No linear relationship between the dependent variable and the independent variables) Ha: βj ≠ 0 (Linear relationship between the dependent variable and at least one of the independent variables)
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This note was uploaded on 03/18/2012 for the course ACCT 515 taught by Professor ? during the Spring '10 term at Keller Graduate School of Management.

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2nd choice - Gm533- Statistic Paper EXECUTIVE SUMMARY...

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