Crimes Vs. Unemployment
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PROPERTY CRIMES
Statistics Managerial
Session: September 2010
TABLE OF CONTENT
Page #
Executive summary
Introduction
Background and problems
Scope
Data design
Data analysis and Inferences
Descriptive analysis of Crimes
Influential statistics
Crimes vs. Unemployment
Conclusion
Reference
Appendices
Executive summary
An analysis was performed to determine to see if the amount of property crimes were higher in states with a larger unemployment rate. The survey results in case 49 were used in determining this hypothesis. The null hypothesis stated there was no increase in unemployment in states with larger property crime rate and there isnt any noticeable increase in unemployment. The alternative hypothesis were stating is that there is a noticeable increase in property crime where there is a higher unemployment rate. We used a simple linear regression analysis to project this hypothesis. The result is that there is no pattern in an increase of property crime to increase in unemployment. We have to reject the alternative hypothesis and accept the null hypothesis. After finding our hypothesis to be rejected, we used a multiple regression analysis to determine what the key factors are that result in a higher crime rate.
Introduction
Background
Crimes are not new to this century. There
are some studies available since 1830 and crimes rate always describe an upward and downward movement. Crime experts have identified a variety of social, economic, personal, and demographic factors that influence crime rate trends. Although, crime experts are still uncertain about how these factors impact these trends, directional change seems to be associated with crime rates.
Scope
How much property crime is there? What are the trends and the patterns in property crime rate? What is the impact of unemployment in crime rate?
These are some of the core issues that will be addressed in this report.
Data design
The raw data for this analysis come from US government sources such as 1988 Uniform Crime reports, Federal Bureau of Investigation, Office of Research and Statistics, Social Security Administration, Commerce Department, and so forth.
These data covered all 50 states in US. For each state, we have data regarding:
Crime rate per hundred thousand inhabitants (CRIMES); property crimes include burglary, larceny, theft, and motor vehicle theft
Capita income (PINCOME)
High school dropout rate (DROPOUT)
Average precipitation in inches in the major cities (PRECIP)
Percentage of public aid recipients (PUBAID)
Density of population (DENSITY)
Public aid for families with children, dollars per family (KIDS)
Percentage of unemployed workers (UNEMPLOY)
Percentage of the residents living in urban areas (URBAN)
Our objective is to analyze property crime. Are the other factors (PINCOME, DROPOUT, PRECIP, PUBAID, DENSITY, KIDS, UNEMPLOY, URBAN) influenced positively or negatively the property crime rate? What are the frequency of occurrence and the reasonable probability that these factors influence property crime rate?
Data analysis and Inferences
Descriptive analysis of Crimes
This is some observations:
Mean: 4,559.2
Dispersion: 1,231.9
Mode: 5705.7
Median: 4365.9
Minimum: 2,017.4
Maximum: 7,819.9
Influential statistics
Regression output
confidence interval
variables
coefficients
p-value
95% lower
95% upper
Intercept
-642.5030
.5339
-2,710.5819
1,425.5760
PINCOME
-0.0183
.8136
-0.1745
0.1378
DROPOUT
81.2926
.0006
36.8914
125.6937
PUBAID
-113.7144
.1561
-272.6524
45.2235
DENSITY
-1.9841
.0096
-3.4583
-0.5100
1.1038
.4504
-1.8215
4.0292
PRECIP
1.5821
.8880
-20.9632
24.1274
UNEMPLOY
-46.3830
.5635
-207.2353
114.4692
URBAN
64.3915
6.18E-07
42.3173
86.4657
We are sure almost 100% that crimes is significantly related to at least one factor (p-value = 2.42E-08 for the overall F test)
63% (correlation R2 = 0.63) of the variability in crime depends on these 8 factors; it is a good relationship.
Capita income is 18.64% related to crime
High school dropout rate 99.94% related to crime
Average precipitation in inches in the major cities 11.2% related to crime
Percentage of public aid recipients 84.39% related to crime
Density of population is 99.04% related to crime
Public aid for families with children, dollars per family is 54.97% related to crime
Percentage of unemployed workers