# Neighborhood Crime Rates Essay

2533 Words Apr 30th, 2015 11 Pages
What variables affect the difference in crime rates throughout the neighborhoods of a city?

By Anna Burns

Introduction:
This project is a focus on how variables such as population, ethnicity, and income affect crime rates throughout different neighborhoods throughout a city. I feel that this information finding this information could be useful to many people. For example if you are looking to buy a new home or even start a new business, you’ll probably want it located in a safe neighborhood. This study will help identify the signs of a safe neighborhood. Knowing why crime rates are higher in some areas may also help prevent the crime rate to rise in other neighborhoods. For example, if crime rates are higher in neighborhoods with
The next model I will be using is Linear Regression. Assuming that more than one of my variables is related to the crime rate, I will use Multiple Linear Regression. The equation I will use (in the circumstance that all variables are related to the crime rate) is:

Average Crime Rate = β0+ β1 Population + β2 Median Income + β3 House Vacancy + β4 Ethnicity + Error

Average Crime Rate = β0+ β1 Population + β2 Median Income + β3 House Vacancy + β4 Ethnicity + Error

The last test I will be using is One-Way Analysis of Variance. This test will help me to see if crime rates in a neighborhood are related to the community in which they are situated.

Descriptive Statistics:
Before applying my tests, here are some graphs and descriptive statistics about my variables:

The mean and the median are pretty close together in the summary. There is one main outlier which is Whittier neighborhood, which has created a right skewed graph.

By looking at the difference in the mean median household income vs. the median median household income you can see that there are more neighborhoods making less than the average household income for the entire city. This skews the graph to the right.

The average percent of vacant houses is around 8.3% which is less than the national rate of 11.4% and the state rate of 11.1% (2010 Census). As you can tell from the graph and the map, there is just one main outlier,

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