Association Between Ethnicity and Crime

This assignment investigates the association between ethnic minority rate and different types of notifiable offenses. It utilizes chi-square tests in SPSS to analyze the provided dataset and determine if there is a statistically significant relationship between these variables. The results are presented with their corresponding p-values, and the findings ultimately conclude that there is no significant association between ethnicity and various reported crimes.

SPSS

TABLE OF CONTENTS
Introduction..........................................................................................................................................
Task 1...................................................................................................................................................
Bivariate Correlation Analysis.....................................................................................................1
Task 2...................................................................................................................................................
Chi Square Test............................................................................................................................2
Task 3...................................................................................................................................................
Chi Square Test............................................................................................................................8
References..........................................................................................................................................

INTRODUCTION
In the present research report, researcher is focusing on evaluating the data related to LAs
– Offences and Census data. This includes, for each local authority (LA) in England and Wales.
Herein, data gathered is related to the notifiable offences rates within different regions of the
country. Furthermore, different notifiable offences, as recorded by the police (absolute number
of offences per (LA) for the period April 2010 – March 2011. A number of variables from the
last UK Census (March 2011), including population size, age structure, population background
and various socio-economic indicators. In this regard, different hypothesis will be prepared and
tested with the help of SPSS tool. Further, to prove the hypothesis various test such as bivariate
correlation, Chi-Square and will be used so that relationship and association between variables
can be identified (Pallant, 2007).
TASK 1
Bivariate Correlation Analysis
Ha0 = Null Hypothesis
Ha1 = Alternative Hypothesis
Hypothesis 2:
Ha0: There is no significant relationship between Unemployment rate of country and the
Notifiable Offences.
Ha1: There is significant relationship between Unemployment rate of country and the Notifiable
Offences.
Descriptive statistics:
Descriptive Statistics
Mean Std. Deviation N
Unemployment rate .0576 .01934 348
Robbery (Notifiable Offences) 219.433 475.9617 344
Correlation:
Correlations
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Unemployment
rate
Robbery
(Notifiable
Offences)
Unemployment rate
Pearson Correlation 1 .463**
Sig. (2-tailed) .000
N 348 344
Robbery (Notifiable Offences)
Pearson Correlation .463** 1
Sig. (2-tailed) .000
N 344 344
**. Correlation is significant at the 0.01 level (2-tailed).
Interpretation:
On the basis of above computation of bivariate correlation, relationship between
unemployment rate and robbery a notifiable offences has been identified. However, the main
purpose of evaluating the relationship between both these variables is to identify whether
unemployment rate forcing or influencing people to make such notifiable offences. In regards to
the Pearson Correlation significance value is 0.463 which indicates there is weak relationship
between both variables. But with the positive significance value indicates that if unemployment
rate of different cities of UK increases, will increase the robbery rate. Further, with the higher
significance value of 0.463 as compared to the significance value of 0.05 (Bivariate Correlation,
2014). This clearly indicates that, alternative hypothesis has been accepted and null rejected
which presents there is statistically significant relations between unemployment rate and robbery
a notifiable offence. Therefore, it can be said that, if unemployment rate in different cities of UK
increases will leads to increase the rate of robbery offence in the places.
TASK 2
Chi Square Test
Chi Square Test:
Ha0 = Null Hypothesis
Ha1 = Alternative Hypothesis
Hypothesis 2:
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Ha0 = There is no significant association between different region of the UK and various
notifiable offences
Ha1 = There is significant association between different region of the UK and various
notifiable offences
Region Code *Violence against the Person
Chi-Square Tests
Value df Asymp. Sig. (2-sided)
Pearson Chi-Square 3015.772a 2988 .357
Likelihood Ratio 1502.543 2988 1.000
Linear-by-Linear Association 1.204 1 .272
N of Valid Cases 348
a. 3330 cells (100.0%) have expected count less than 5. The minimum expected count is .03.
Findings:
On the basis of above chi square test it has been identified that, with high significance
value of 0.357 as compared to 0.05 it has been evaluated that there is no significant association
between region code and violence against the person.
Region Code *Act Endangering Life
Chi-Square Tests
Value df Asymp. Sig. (2-sided)
Pearson Chi-Square 1384.839a 1206 .000
Likelihood Ratio 904.889 1206 1.000
Linear-by-Linear Association 4.472 1 .034
N of Valid Cases 344
a. 1350 cells (100.0%) have expected count less than 5. The minimum expected count is .03.
Findings:
On the basis of above chi square test it has been identified that, with low significance
value of 0.000 as compared to 0.05 it has been evaluated that there is significant association
between region code and act endangering life.
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Region Code *Other Wounding
Chi-Square Tests
Value df Asymp. Sig. (2-sided)
Pearson Chi-Square 2925.253a 2844 .141
Likelihood Ratio 1470.252 2844 1.000
Linear-by-Linear Association 4.521 1 .033
N of Valid Cases 346
a. 3170 cells (100.0%) have expected count less than 5. The minimum expected count is .03.
Findings:
On the basis of above chi square test it has been identified that, with high significance
value of 0.141 as compared to 0.05 it has been evaluated that there is no significant association
between region code and other wounding.
Region Code *Harassment
Chi-Square Tests
Value df Asymp. Sig. (2-sided)
Pearson Chi-Square 2602.473a 2592 .439
Likelihood Ratio 1387.387 2592 1.000
Linear-by-Linear Association .444 1 .505
N of Valid Cases 346
a. 2890 cells (100.0%) have expected count less than 5. The minimum expected count is .03.
Findings:
On the basis of above chi square test it has been identified that, with high significance
value of 0.439 as compared to 0.05 it has been evaluated that there is no significant association
between region code and harassment.
Region Code *Assault
Chi-Square Tests
Value df Asymp. Sig. (2-sided)
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Pearson Chi-Square 2722.324a 2700 .378
Likelihood Ratio 1422.751 2700 1.000
Linear-by-Linear Association .045 1 .833
N of Valid Cases 346
a. 3010 cells (100.0%) have expected count less than 5. The minimum expected count is .03.
Findings:
On the basis of above chi square test it has been identified that, with high significance
value of 0.378 as compared to 0.05 it has been evaluated that there is no significant association
between region code and Assault.
Region Code *Robbery
Chi-Square Tests
Value df Asymp. Sig. (2-sided)
Pearson Chi-Square 1795.410a 1683 .028
Likelihood Ratio 1086.700 1683 1.000
Linear-by-Linear Association .049 1 .825
N of Valid Cases 344
a. 1880 cells (100.0%) have expected count less than 5. The minimum expected count is .03.
Findings:
On the basis of above chi square test it has been identified that, with low significance
value of 0.028 as compared to 0.05 it has been evaluated that there is significant association
between region code and Robbery.
Region Code * Theft
Chi-Square Tests
Value df Asymp. Sig. (2-sided)
Pearson Chi-Square 1861.726a 1818 .233
Likelihood Ratio 1113.502 1818 1.000
Linear-by-Linear Association .002 1 .963
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N of Valid Cases 346
a. 2030 cells (100.0%) have expected count less than 5. The minimum expected count is .03.
Findings:
On the basis of above chi square test it has been identified that, with high significance
value of 0.233 as compared to 0.05 it has been evaluated that there is no significant association
between region code and Theft.
Region Code *Damage
Chi-Square Tests
Value df Asymp. Sig. (2-sided)
Pearson Chi-Square 2955.779a 2934 .385
Likelihood Ratio 1494.225 2934 1.000
Linear-by-Linear Association 16.185 1 .000
N of Valid Cases 348
a. 3270 cells (100.0%) have expected count less than 5. The minimum expected count is .03.
Findings:
On the basis of above chi square test it has been identified that, with high significance
value of 0.385 as compared to 0.05 it has been evaluated that there is no significant association
between region code and Damage.
Region Code *Burglarly
Chi-Square Tests
Value df Asymp. Sig. (2-sided)
Pearson Chi-Square 2755.737a 2736 .392
Likelihood Ratio 1432.861 2736 1.000
Linear-by-Linear Association 7.108 1 .008
N of Valid Cases 348
a. 3050 cells (100.0%) have expected count less than 5. The minimum expected count is .03.
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Findings:
On the basis of above chi square test it has been identified that, with high significance
value of 0.392 as compared to 0.05 it has been evaluated that there is no significant association
between region code and Burglarly.
Region Code *Burglarly other than a dwelling
Chi-Square Tests
Value df Asymp. Sig. (2-sided)
Pearson Chi-Square 2727.229a 2682 .267
Likelihood Ratio 1416.839 2682 1.000
Linear-by-Linear Association 13.699 1 .000
N of Valid Cases 346
a. 2990 cells (100.0%) have expected count less than 5. The minimum expected count is .03.
Findings:
On the basis of above chi square test it has been identified that, with high significance
value of 0.392 as compared to 0.05 it has been evaluated that there is no significant association
between region code and Burglarly other than a dwelling.
Region Code *Theft of vehicles
Chi-Square Tests
Value df Asymp. Sig. (2-sided)
Pearson Chi-Square 2420.982a 2322 .075
Likelihood Ratio 1319.672 2322 1.000
Linear-by-Linear Association 3.056 1 .080
N of Valid Cases 348
a. 2590 cells (100.0%) have expected count less than 5. The minimum expected count is .03.
Findings:
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On the basis of above chi square test it has been identified that, with high significance
value of 0.075 as compared to 0.05 it has been evaluated that there is no significant association
between region code and theft of vehicles.
Region Code *Theft from a vehicle
Chi-Square Tests
Value df Asymp. Sig. (2-sided)
Pearson Chi-Square 2742.400a 2709 .322
Likelihood Ratio 1421.705 2709 1.000
Linear-by-Linear Association 1.871 1 .171
N of Valid Cases 346
a. 3020 cells (100.0%) have expected count less than 5. The minimum expected count is .03.
Findings:
On the basis of above chi square test it has been identified that, with high significance
value of 0.322 as compared to 0.05 it has been evaluated that there is no significant association
between region code and theft from a vehicles.
Interpretation:
On the basis of above computation of chi square test, association between different cities
of UK and various notifiable offences has been evaluated (Dretzke, 2009). However, the results
identified indicates that in several cities of UK is not associated with different notifiable offences
which means these places are safe and secure. Thus, high significance value than 0.05 in most of
the notifiable offences indicates that there is no significance association between the variables
and leads to accept null hypothesis and rejected the alternative hypothesis (Chi-Square Test,
2014).
TASK 3
Chi Square Test
Ha0 = Null Hypothesis
Ha1 = Alternative Hypothesis
Hypothesis 2:
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Ha0 = There is no significant association between ethnic minority rate and various notifiable
offences
Ha1 = There is significant association between ethnic minority rate and various notifiable
offences
Ethnic minority rate * Violence Agains the Person
Chi-Square Tests
Value df Asymp. Sig. (2-sided)
Pearson Chi-Square 115536.000a 115204 .244
Likelihood Ratio 4031.544 115204 1.000
Linear-by-Linear Association 132.830 1 .000
N of Valid Cases 348
a. 115884 cells (100.0%) have expected count less than 5. The minimum expected count is .00.
Findings:
On the basis of above chi square test it has been identified that, with high significance
value of 0.244 as compared to 0.05 it has been evaluated that there is no significant association
between ethnic minority rate and violence against the person.
Ethnic minority rate * Act Endangering Life
Chi-Square Tests
Value df Asymp. Sig. (2-sided)
Pearson Chi-Square 46096.000a 45962 .329
Likelihood Ratio 3170.038 45962 1.000
Linear-by-Linear Association 93.131 1 .000
N of Valid Cases 344
a. 46440 cells (100.0%) have expected count less than 5. The minimum expected count is .00.
Findings:
On the basis of above chi square test it has been identified that, with high significance
value of 0.329 as compared to 0.05 it has been evaluated that there is no significant association
between ethnic minority rate and act endangering life.
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Ethnic minority rate * Other Wounding
Chi-Square Tests
Value df Asymp. Sig. (2-sided)
Pearson Chi-Square 109336.000a 109020 .249
Likelihood Ratio 3964.284 109020 1.000
Linear-by-Linear Association 85.468 1 .000
N of Valid Cases 346
a. 109682 cells (100.0%) have expected count less than 5. The minimum expected count is .00.
Findings:
On the basis of above chi square test it has been identified that, with high significance
value of 0.249 as compared to 0.05 it has been evaluated that there is no significant association
between ethnic minority rate and other wounding.
Ethnic minority rate * Harassment
Chi-Square Tests
Value df Asymp. Sig. (2-sided)
Pearson Chi-Square 99648.000a 99360 .259
Likelihood Ratio 3880.373 99360 1.000
Linear-by-Linear Association 153.403 1 .000
N of Valid Cases 346
a. 99994 cells (100.0%) have expected count less than 5. The minimum expected count is .00.
Findings:
On the basis of above chi square test it has been identified that, with high significance
value of 0.259 as compared to 0.05 it has been evaluated that there is no significant association
between ethnic minority rate and harassment.
Ethnic minority rate * Assault
Chi-Square Tests
Value df Asymp. Sig. (2-sided)
Pearson Chi-Square 103800.000a 103500 .255
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Likelihood Ratio 3914.011 103500 1.000
Linear-by-Linear Association 153.782 1 .000
N of Valid Cases 346
a. 104146 cells (100.0%) have expected count less than 5. The minimum expected count is .00.
Findings:
On the basis of above chi square test it has been identified that, with high significance
value of 0.255 as compared to 0.05 it has been evaluated that there is no significant association
between ethnic minority rate and assault.
Ethnic minority rate * Robbery
Chi-Square Tests
Value df Asymp. Sig. (2-sided)
Pearson Chi-Square 64328.000a 64141 .300
Likelihood Ratio 3443.612 64141 1.000
Linear-by-Linear Association 188.845 1 .000
N of Valid Cases 344
a. 64672 cells (100.0%) have expected count less than 5. The minimum expected count is .00.
Findings:
On the basis of above chi square test it has been identified that, with high significance
value of 0.300 as compared to 0.05 it has been evaluated that there is no significant association
between ethnic minority rate and assault.
Ethnic minority rate * Theft
Chi-Square Tests
Value df Asymp. Sig. (2-sided)
Pearson Chi-Square 69892.000a 69690 .294
Likelihood Ratio 3534.863 69690 1.000
Linear-by-Linear Association 129.040 1 .000
N of Valid Cases 346
a. 70238 cells (100.0%) have expected count less than 5. The minimum expected count is .00.
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Findings:
On the basis of above chi square test it has been identified that, with high significance
value of 0.294 as compared to 0.05 it has been evaluated that there is no significant association
between ethnic minority rate and theft.
Ethnic minority rate * Damage
Chi-Square Tests
Value df Asymp. Sig. (2-sided)
Pearson Chi-Square 113448.000a 113122 .246
Likelihood Ratio 4014.909 113122 1.000
Linear-by-Linear Association 32.892 1 .000
N of Valid Cases 348
a. 113796 cells (100.0%) have expected count less than 5. The minimum expected count is .00.
Findings:
On the basis of above chi square test it has been identified that, with high significance
value of 0.246 as compared to 0.05 it has been evaluated that there is no significant association
between ethnic minority rate and theft.
Ethnic minority rate * Burglarly
Chi-Square Tests
Value df Asymp. Sig. (2-sided)
Pearson Chi-Square 105792.000a 105488 .254
Likelihood Ratio 3950.772 105488 1.000
Linear-by-Linear Association 110.707 1 .000
N of Valid Cases 348
a. 106140 cells (100.0%) have expected count less than 5. The minimum expected count is .00.
Findings:
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On the basis of above chi square test it has been identified that, with high significance
value of 0.254 as compared to 0.05 it has been evaluated that there is no significant association
between ethnic minority rate and burglarly.
Ethnic minority rate * Burglary other than a dwelling
Chi-Square Tests
Value df Asymp. Sig. (2-sided)
Pearson Chi-Square 103108.000a 102810 .255
Likelihood Ratio 3908.098 102810 1.000
Linear-by-Linear Association 33.107 1 .000
N of Valid Cases 346
a. 103454 cells (100.0%) have expected count less than 5. The minimum expected count is .00.
Findings:
On the basis of above chi square test it has been identified that, with high significance
value of 0.255 as compared to 0.05 it has been evaluated that there is no significant association
between ethnic minority rate and burglarly other than a dwelling.
Ethnic minority rate * Theft of vehicle
Chi-Square Tests
Value df Asymp. Sig. (2-sided)
Pearson Chi-Square 89784.000a 89526 .271
Likelihood Ratio 3793.222 89526 1.000
Linear-by-Linear Association 139.153 1 .000
N of Valid Cases 348
a. 90132 cells (100.0%) have expected count less than 5. The minimum expected count is .00.
Findings:
On the basis of above chi square test it has been identified that, with high significance
value of 0.271 as compared to 0.05 it has been evaluated that there is no significant association
between ethnic minority rate and theft of vehicle.
Ethnic minority rate * Theft from a vehicle
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