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Neighborhood Crime Rates Essay

2544 words - 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 ...view middle of the document...

The first model will be Chi-Square Test of Independence, which will help me find if the categorical variables are associated in any way. 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, Downtown East.

For ethnicity, I only am displaying the percent f population that is white since the percentage of white occupants on average is greater than all of the other races combined. With white being the predominate race, the graph is slightly left skewed. When I test to see if ethnicity has an effect on crime rates, I will test Hispanic/Latino, Black/African American, and Asian ethnicities.

Estimation:
The first test I will perform is Chi-Square test of independence to compare my categorical data I have against above and below median crime rates. I will be testing above and below averages for population, income, percent white, percent black/African American, percent Hispanic/Latino, percent Asian. I will also be testing direction.
H0: There is no association between the row variable and the column variable.
H1: There is an association between the row variable and the column variable.
H0: There is no association between the row variable and the column variable.
H1: There is an association between the row variable and the column variable.

To test the null hypothesis, if the P-Value of the test is less than 0.05 I will reject the null hypothesis.

Tabulated statistics: PopCat, CrimeCat

Rows: PopCat Columns: CrimeCat

Above Below
Median Median
Crime R Crime R All

Above Median Pop 25 15 40
...

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