Crime in States

7/30/2019 Crime in States

1/13

Statistical analysis of the

relation between Crime Rate,Education and Poverty: USA,

2009

Sonarika Mahajan

100076


2/13

Research Question

In this research paper, analysis is done to conclude whether the level of education and

poverty influence the total crime rate in the United States of America. Using descriptive

statistics such a mean, standard deviation, variance, histograms, scatter diagrams and simple

linear regression analysis performed upon both independent variables separately, it can be

analysed till what extent do these two independent variables, i.e. education and poverty cause

fluctuations upon the dependent variable, in what proportion (direct or inverse) and of the

two independent variables, which is a better predictor for determining crime rate in USA.

Data description

[The states selected for this study are highlighted with yellow in the above map]

The Data that is used to define our dependent variable include both, violent crime (murder

and non- negligent manslaughter, forcible rape, robbery, and aggravated assault) as well as

property crime (burglary, larceny-theft, motor vehicle theft, and arson). Crime statistics used

in this study are published by FBI (Federal Bureau of Intelligence) serving as a governmental

agency to the United States Department of Justice.

The independent variable that comments upon the education levels in the United States of

America is carried out by analysing the total number of public high school graduates per

state. This data includes students of all the ethnicities for the school year 2008-2009. The

education universe in this study is equivalent to the total population of the state. This data has

been collected by National Centre for Education Statistics (NCES), which is the primary

federal entity that collects education related data in the U.S. and other countries and analyses

it.


3/13

The poverty status for an individual is measured by comparing his/her income to a preset

amount of dollars known as the threshold value. The poverty universe excludes children

below the age of 15, people living in military barracks, institutional group quarters and

college dormitories. This data is collected by the U.S. Census Bureau, serving as the most

reliable source about Americas people and economy.

All the data collected is cross-sectional, since it was taken during the same time period (year

2009) across different parameters. Also, the scale of measurement for these variables is the

ratio scale, since the ratio between two values is meaningful and the observations are

comparable to a zero value.

Analysis

Mean: It is the representative of a central value for a given data set, i.e. average.

The mean value for crime variable suggests that in the year 2009, the percentage of crimes

being reported in any state of USA was 3.26%.

The mean value for education variable suggests that the percentage of public high school

graduates being reported in any state of USA was 1% for the same time period.

Similarly, the mean value for the poverty variable suggests that the percentage of individuals

living below the poverty line being reported in any state of USA was 13.54%.

Standard deviation & Variance: The higher the value of the standard deviation, greater is the

dispersion of the data set. Out of the three variables, poverty has the highest standard

deviation value of 2.98. Therefore, the percentage of individuals below poverty level is more

widely dispersed over the states as compared to the other two variables.

Variance is the average of the sum of squared deviation scores. It is used to compute the

standard variation since its a better means for determining the dispersion of data. It is

measured as the square of standard deviation for any data set.


4/13

Skewness: The symmetry of the variable distribution is measured by the help of this statistic.

Crime rate has a skewness of 0.083, making it a symmetrical distributed variable since the

value is closer to zero.

The education variable is skewed negatively at -.367 since the variable has lower values,

indicating a left skewed histogram.

Whereas, poverty shows a positive skewness value of .670 since its variables have numerous

high values, which justifies the right skewness of the histogram.


5/13

Simple linear regression model:

a. Crime and Education -

Y = Dependent variable, CrimeX = Independent variable, Education.

The regression model is the equation that describes how y is related to x.

This regression equation is:

From Table 2.4 in appendix, the regression equation is,

Crime = 6.17 - 2.9 (Education)

This regression equation can be graphed as follows assuming 0as the intercept and 1 as the

slope:

Interpretation of the slope: For every 1% increase in the number of students being graduated

from high school, there is a decrease of 2.9% in crime activities in the USA.

Interpretation of the intercept: Even if there is no variation in the education level, the

estimated crime rate would be 6.17%.

The coefficient of determination or r2: It determines the proportion of variation in the

dependent variable by the independent variable.

From Table 2.2, r2

= .181

This states that 18.1% of the variation in crime rate is explained by regression of education

on crime. Since this value is not close to 1, it doesnt seem to be a appropriate predictortodetermine the crime rate in USA.

Here the slope 1

is negative.


6/13

Hypothesis testing:

Ho: 1 = 0 (education is not a useful predictor of crime)

Ha: 1 0 (education is a useful predictor of crime)

Significance level: = 0.05

According to the rejection rule, the null hypothesis will be rejected if p-value .

From table 2.4, p-value = 0.019

Since 0.019 0.05, we reject the null hypothesis.

At 95% confidence level, there is enough evidence to conclude that education is a useful

predictor for crime in USA since the slope of the regression line is not zero.

b. Crime and Poverty:

Y = Dependent variable, Crime

X = Independent variable, Poverty.

The regression equation is as follows:

Plugging in the values to from Table 3.4, get:Crime = 1.819 + 0.107 (Poverty)

This regression equation can be graphed as follows assuming 0 as the intercept and 1 as the

slope:

Here the slope 1

is positive.


7/13

Interpretation of the slope: For every 1% increase in the individuals below poverty line, there

is an increase of .11% in crime activities in the USA.

Interpretation of the intercept: With the poverty level remaining constant, the estimated crime

rate would be 1.82%.

The coefficient of determination or r2

From Table 3.2, r2

= .191

This states that 19.1% of the variation in crime rate is explained by regression of poverty on

crime.

Hypothesis testing:

Ho: 1 = 0 (poverty is not a useful predictor of crime)

Ha: 1 0 (poverty is a useful predictor of crime)

Significance level: = 0.05

According to the rejection rule, the null hypothesis will be rejected if p-value .From table 3.4, p-value = 0.016

Since 0.016 0.05, we reject the null hypothesis.

At 95% confidence level, there is enough evidence to conclude that poverty is a useful

predictor for crime in USA since the slope of the regression line is not zero.

Conclusion and recommendations

From this study conducted, it is assured that the crime rate in USA is directly proportionate to

the people below the poverty line and inversely proportionate to the number of high school

students graduating in the year 2009. When simple linear regression was performed to both

the independent variables separately, the coefficient of determination (r2) and the p-value

aided our study to select the variable that was a better predictor for determining the crime rate

in America. Poverty, with the significance level of 19.1% is known to be a better predictor in

this case as compared to the 18.1% significance level shown by the independent variable,

education. This fact was further proved when the p-value for poverty stood at a lower

amount as compared to its counterpart.

Even though it can be concluded that poverty is a better predictor for crime rate in USA, thelevel of significance still stands at a diminutive 19.1%. Much stronger predictors could be

used for the above study. GDP, income level, provision of federal aid or employment rate

could be a few options to choose amongst.


8/13

Appendix

Table 1.1 Statistics for crimes reported in 30 states of USA.

State Population ViolentCrime PropertyCrime Total CrimePercentage ofTotal Crime

Alabama 47,08,708 21,179 1,77,629 1,98,808 4.22

Alaska 6,98,473 4,421 20,577 24,998 3.58

Arizona 65,95,778 26,929 2,34,582 2,61,511 3.96

California 3,69,61,664 1,74,459 10,09,614 11,84,073 3.20

Colorado 50,24,748 16,976 1,33,968 1,50,944 3.00

Connecticut 35,18,288 10,508 82,181 92,689 2.63

Florida 1,85,37,969 1,13,541 7,12,010 8,25,551 4.45Hawaii 12,95,178 3,559 47,419 50,978 3.94

Iowa 30,07,856 8,397 69,441 77,838 2.59

Kansas 28,18,747 11,278 90,420 1,01,698 3.61

Michigan 99,69,727 49,547 2,82,918 3,32,465 3.33

Minnesota 52,66,214 12,842 1,39,083 1,51,925 2.88

Mississippi 29,51,996 8,304 87,181 95,485 3.23

Missouri 59,87,580 29,444 2,02,698 2,32,142 3.88

Montana 9,74,989 2,473 24,024 26,497 2.72

Nebraska 17,96,619 5,059 49,614 54,673 3.04

Nevada 26,43,085 18,559 80,763 99,322 3.76

New Jersey 87,07,739 27,121 1,81,097 2,08,218 2.39

New Mexico 20,09,671 12,440 75,078 87,518 4.35

New York 1,95,41,453 75,176 3,78,315 4,53,491 2.32

North

Carolina

93,80,884 37,929 3,44,098 3,82,027 4.07

North

Dakota

6,46,844 1,298 12,502 13,800 2.13

Oregon 38,25,657 9,744 1,13,511 1,23,255 3.22

Pennsylvania1,26,04,767 47,965 2,77,512 3,25,477 2.58

South

Dakota

8,12,383 1,508 13,968 15,476 1.91

Texas 2,47,82,302 1,21,668 9,95,145 11,16,813 4.51

Virginia 78,82,590 17,879 1,91,453 2,09,332 2.66

Washington 66,64,195 22,056 2,44,368 2,66,424 4.00

Wisconsin 56,54,774 14,533 1,47,486 1,62,019 2.87

Wyoming 5,44,270 1,242 14,354 15,596 2.87

Source:http://www.fbi.gov/about-us/cjis/ucr/crime-in-the-u.s/2011/crime-in-the-u.s.-2011/tables/table-5
http://www.fbi.gov/about-us/cjis/ucr/crime-in-the-u.s/2011/crime-in-the-u.s.-2011/tables/table-5http://www.fbi.gov/about-us/cjis/ucr/crime-in-the-u.s/2011/crime-in-the-u.s.-2011/tables/table-5http://www.fbi.gov/about-us/cjis/ucr/crime-in-the-u.s/2011/crime-in-the-u.s.-2011/tables/table-5http://www.fbi.gov/about-us/cjis/ucr/crime-in-the-u.s/2011/crime-in-the-u.s.-2011/tables/table-5


9/13

Table 1.2 Statistics for public high school graduates in 30 states of USA.

State Population Total Public

High

School

Graduates

Percentage of

High School

Graduates

Alabama 47,08,708 42,082 0.89

Alaska 6,98,473 8,008 1.15

Arizona 65,95,778 62,374 0.95

California 3,69,61,664 3,72,310 1.01

Colorado 50,24,748 47,459 0.94

Connecticut 35,18,288 34,968 0.99

Florida 1,85,37,969 1,53,461 0.83

Hawaii 12,95,178 11,508 0.89

Iowa 30,07,856 33,926 1.13

Kansas 28,18,747 30,368 1.08

Michigan 99,69,727 1,12,742 1.13

Minnesota 52,66,214 59,729 1.13

Mississippi 29,51,996 24,505 0.83

Missouri 59,87,580 62,969 1.05

Montana 9,74,989 10,077 1.03

Nebraska 17,96,619 19,501 1.09

Nevada 26,43,085 19,904 0.75

New Jersey 87,07,739 95,085 1.09

New Mexico 20,09,671 17,931 0.89New York 1,95,41,453 1,80,917 0.93

North

Carolina

93,80,884 86,712 0.92

North

Dakota

6,46,844 7,232 1.12

Oregon 38,25,657 35,138 0.92

Pennsylvania 1,26,04,767 1,30,658 1.04

South

Dakota

8,12,383 8,123 1.00

Texas 2,47,82,302 2,64,275 1.07

Virginia 78,82,590 79,651 1.01

Washington 66,64,195 62,764 0.94

Wisconsin 56,54,774 65,410 1.16

Wyoming 5,44,270 5,493 1.01

Source:http://nces.ed.gov/CCD/tables/ESSIN_Task5_f2.asp
http://nces.ed.gov/CCD/tables/ESSIN_Task5_f2.asphttp://nces.ed.gov/CCD/tables/ESSIN_Task5_f2.asphttp://nces.ed.gov/CCD/tables/ESSIN_Task5_f2.asphttp://nces.ed.gov/CCD/tables/ESSIN_Task5_f2.asp


10/13

Table 1.3 Statistics for individuals below Poverty line in 30 states of USA.

State Population for

whom poverty

status isdetermined

Individuals

in poverty

Percent

below

poverty

Alabama 45,88,899 8,04,683 17.54

Alaska 6,82,412 61,653 9.03

Arizona 64,75,485 10,69,897 16.52

California 3,62,02,780 51,28,708 14.17

Colorado 49,17,061 6,34,387 12.90

Connecticut 34,09,901 3,20,554 9.40

Florida 1,81,24,789 27,07,925 14.94

Hawaii 12,64,202 1,31,007 10.36

Iowa 29,05,436 3,42,934 11.80

Kansas 27,32,685 3,65,033 13.36

Michigan 97,35,741 15,76,704 16.20

Minnesota 51,33,038 5,63,006 10.97

Mississippi 28,48,335 6,24,360 21.92

Missouri 58,18,541 8,49,009 14.59

Montana 9,46,333 1,43,028 15.11

Nebraska 17,39,311 2,14,765 12.35

Nevada 26,06,479 3,21,940 12.35New Jersey 85,31,160 7,99,099 9.37

New Mexico 19,68,078 3,53,594 17.97

New York 1,90,14,215 26,91,757 14.16

North Carolina 90,95,948 14,78,214 16.25

North Dakota 6,20,821 72,342 11.65

Oregon 37,48,545 5,34,594 14.26

Pennsylvania 1,21,65,877 15,16,705 12.47

South Dakota 7,82,725 1,11,305 14.22

Texas 2,41,76,222 41,50,242 17.17

Virginia 76,23,736 8,02,578 10.53

Washington 65,30,664 8,04,237 12.31

Wisconsin 54,95,845 6,83,408 12.43

Wyoming 5,29,982 52,144 9.84

Source:

http://www.census.gov/compendia/statab/cats/income_expenditures_poverty_wealth/income_and

_poverty--state_and_local_data.html
http://www.census.gov/compendia/statab/cats/income_expenditures_poverty_wealth/income_and_poverty--state_and_local_data.htmlhttp://www.census.gov/compendia/statab/cats/income_expenditures_poverty_wealth/income_and_poverty--state_and_local_data.htmlhttp://www.census.gov/compendia/statab/cats/income_expenditures_poverty_wealth/income_and_poverty--state_and_local_data.htmlhttp://www.census.gov/compendia/statab/cats/income_expenditures_poverty_wealth/income_and_poverty--state_and_local_data.htmlhttp://www.census.gov/compendia/statab/cats/income_expenditures_poverty_wealth/income_and_poverty--state_and_local_data.html


11/13

Regression (Independent variable: Education)

Table 2.1

Variables Entered/Removedb

Model

Variables

Entered

Variables

Removed Method

1 Educationa

. Enter

a. All requested variables entered.

b. Dependent Variable: Crime

Table 2.2

Model Summary

Model R R Square

Adjusted R

Square

Std. Error of the

Estimate

1 .425a

.181 .152 .67068

a. Predictors: (Constant), Education

Table 2.3

ANOVAb

Model Sum of Squares df Mean Square F Sig.

1 Regression 2.784 1 2.784 6.189 .019a

Residual 12.595 28 .450

Total 15.379 29

a. Predictors: (Constant), Education


Table 2.4

Coefficientsa

Model

Unstandardized Coefficients

Standardized

Coefficients

t Sig.B Std. Error Beta

1 (Constant) 6.165 1.173 5.257 .000

Education -2.904 1.167 -.425 -2.488 .019


12/13

Regression (Independent variable: Poverty)

Table 3.1

Variables Entered/Removed

b

Model

Variables

Entered

Variables

Removed Method

1 Povertya

. Enter

a. All requested variables entered.


Table 3.2

Model Summary

Model R R Square

Adjusted R

Square

Std. Error of the

Estimate

1 .437a

.191 .162 .66665

a. Predictors: (Constant), Poverty

Table 3.3

ANOVAb

Model Sum of Squares df Mean Square F Sig.

1 Regression 2.935 1 2.935 6.604 .016a

Residual 12.444 28 .444

Total 15.379 29

a. Predictors: (Constant), Poverty


Table 3.4

Coefficientsa

Model

Unstandardized Coefficients

Standardized

Coefficients

t Sig.B Std. Error Beta

1 (Constant) 1.819 .575 3.162 .004

Poverty .107 .042 .437 2.570 .016

a. Dependent Variable: Crime


13/13

Bibliography

1. FBITable 5. 2012. FBITable 5. [ONLINE] Available at:http://www.fbi.gov/about-

us/cjis/ucr/crime-in-the-u.s/2011/crime-in-the-u.s.-2011/tables/table-5. [Accessed 28

November 2012].

2. Income and Poverty--State and Local Data - The 2012 Statistical Abstract - U.S. Census

Bureau. 2012.Income and Poverty--State and Local Data - The 2012 Statistical Abstract

- U.S. Census Bureau. [ONLINE] Available

at:http://www.census.gov/compendia/statab/cats/income_expenditures_poverty_wealth/in

come_and_poverty--state_and_local_data.html. [Accessed 28 November 2012].

3. Table 2.Number of public high school graduates, by race/ethnicity, gender, and state:

School years 199293 through 200809. 2012. Table 2.Number of public high school

graduates, by race/ethnicity, gender, and state: School years 199293 through 200809.

[ONLINE] Available at:http://nces.ed.gov/CCD/tables/ESSIN_Task5_f2.asp. [Accessed

28 November 2012].

4. World's best economies - United States: Largest economy (3) - CNNMoney.

2012. World's best economies - United States: Largest economy (3) - CNNMoney.

[ONLINE] Available at:http://money.cnn.com/gallery/news/economy/2012/08/13/worlds-

best-economies/3.html. [Accessed 28 November 2012].

5. Total crimes statistics - countries compared - NationMaster Crime. 2012.Total crimes

statistics - countries compared - NationMaster Crime. [ONLINE] Available

at:http://www.nationmaster.com/graph/cri_tot_cri-crime-total-crimes. [Accessed 28

November 2012].

6. Interactivate: Histogram. 2012.Interactivate: Histogram. [ONLINE] Available

at:http://www.shodor.org/interactivate/activities/Histogram/. [Accessed 28 November

2012].
http://www.fbi.gov/about-us/cjis/ucr/crime-in-the-u.s/2011/crime-in-the-u.s.-2011/tables/table-5http://www.fbi.gov/about-us/cjis/ucr/crime-in-the-u.s/2011/crime-in-the-u.s.-2011/tables/table-5http://www.fbi.gov/about-us/cjis/ucr/crime-in-the-u.s/2011/crime-in-the-u.s.-2011/tables/table-5http://www.fbi.gov/about-us/cjis/ucr/crime-in-the-u.s/2011/crime-in-the-u.s.-2011/tables/table-5http://www.census.gov/compendia/statab/cats/income_expenditures_poverty_wealth/income_and_poverty--state_and_local_data.htmlhttp://www.census.gov/compendia/statab/cats/income_expenditures_poverty_wealth/income_and_poverty--state_and_local_data.htmlhttp://www.census.gov/compendia/statab/cats/income_expenditures_poverty_wealth/income_and_poverty--state_and_local_data.htmlhttp://www.census.gov/compendia/statab/cats/income_expenditures_poverty_wealth/income_and_poverty--state_and_local_data.htmlhttp://nces.ed.gov/CCD/tables/ESSIN_Task5_f2.asphttp://nces.ed.gov/CCD/tables/ESSIN_Task5_f2.asphttp://nces.ed.gov/CCD/tables/ESSIN_Task5_f2.asphttp://money.cnn.com/gallery/news/economy/2012/08/13/worlds-best-economies/3.htmlhttp://money.cnn.com/gallery/news/economy/2012/08/13/worlds-best-economies/3.htmlhttp://money.cnn.com/gallery/news/economy/2012/08/13/worlds-best-economies/3.htmlhttp://money.cnn.com/gallery/news/economy/2012/08/13/worlds-best-economies/3.htmlhttp://www.nationmaster.com/graph/cri_tot_cri-crime-total-crimeshttp://www.nationmaster.com/graph/cri_tot_cri-crime-total-crimeshttp://www.nationmaster.com/graph/cri_tot_cri-crime-total-crimeshttp://www.shodor.org/interactivate/activities/Histogram/http://www.shodor.org/interactivate/activities/Histogram/http://www.shodor.org/interactivate/activities/Histogram/http://www.shodor.org/interactivate/activities/Histogram/http://www.nationmaster.com/graph/cri_tot_cri-crime-total-crimeshttp://money.cnn.com/gallery/news/economy/2012/08/13/worlds-best-economies/3.htmlhttp://money.cnn.com/gallery/news/economy/2012/08/13/worlds-best-economies/3.htmlhttp://nces.ed.gov/CCD/tables/ESSIN_Task5_f2.asphttp://www.census.gov/compendia/statab/cats/income_expenditures_poverty_wealth/income_and_poverty--state_and_local_data.htmlhttp://www.census.gov/compendia/statab/cats/income_expenditures_poverty_wealth/income_and_poverty--state_and_local_data.htmlhttp://www.fbi.gov/about-us/cjis/ucr/crime-in-the-u.s/2011/crime-in-the-u.s.-2011/tables/table-5http://www.fbi.gov/about-us/cjis/ucr/crime-in-the-u.s/2011/crime-in-the-u.s.-2011/tables/table-5

Documents

Crime in States