Prevalence of Local Crimes in England and Wales: A Statistical Analysis

The purpose of this report is to investigate the prevalence of local crimes in England and Wales in recent years. The study involved both male and female respondents of a wide range of age bracket. The statistical analyses that have been conducted as well as the justification for conducting the analyses are also well covered in the introduction section. The statistical analyses that have been done include the frequency analysis, t-test, ANOVA test, cross tabulation, and correlation analysis.

Assessment 1
Data Analysis
Institution Name:
Student Name:
Word Count: 5489

Abstract
The purpose of this report is to investigate the prevalence of local crimes in England and Wales
in recent years. The study involved both male and female respondents of a wide range of age
bracket. The introduction section of the report outlines the nature and type of variables that made
up the sample as well as other finer details about the sample. The statistical analyses that have
been conducted as well as the justification for conducting the analyses are also well covered in
the introduction section. The statistical analyses that have been done include the frequency
analysis, t-test, ANOVA test, cross tabulation, and correlation analysis.
Most of the analyses focused on comparing the prevalence of the crimes among the males and
females at different ages. Similarly, the analyses focused on comparing the opinions of the males
and females concerning the crimes incidences of local crimes and their trust in the police. The
finer details of the results of the analyses are outlined in the analysis chapter and further
discussion of the results has been dealt with in the concluding chapter. However, it is important
to point out that the results revealed that there was no gender that was over or under-represented
as the sample was unbiased.

Contents
Abstract.......................................................................................................................................................2
Introduction.................................................................................................................................................4
Literature Review........................................................................................................................................5
Data analysis...............................................................................................................................................6
Frequencies..............................................................................................................................................6
Gender Frequencies.............................................................................................................................6
Frequencies.................................................................................................................................................7
T-Test........................................................................................................................................................11
Oneway Analysis of Variance (ANOVA).................................................................................................12
Analysis of Variance (ANOVA)................................................................................................................15
Crosstabs...................................................................................................................................................18
Correlations...............................................................................................................................................20
Conclusion.................................................................................................................................................22
References.................................................................................................................................................26
Appendix...................................................................................................................................................28
Appendix 1: Gender Frequency case processing...................................................................................28
Appendix 2: Vehicle stolen or not case processing................................................................................28
Appendix 3: ANOVA Test one Statistics..............................................................................................28
Appendix 4: Post Hoc test Statistics......................................................................................................28
Appendix 5: Cross Tabulation Case Processing Summary....................................................................29

Introduction
The dataset used in this analysis had a total of 33420 respondents. The number of male
respondents was 11791 while the number of female respondents was 1192. The dataset consists
of several variables such as the gender of the respondent, the age of the respondent, the age of
the offender and the financial damage as a result of criminal activity just to mention a few.
The analysis that was conducted includes frequency analysis, Analysis of variance (ANOVA),
independent-test, correlation analysis, and cross-tabulation.
Frequency analysis technique is the study of the counts or the numbers of the variables
(Kovartsev, et al., 2015). Frequency analysis is conducted to demonstrate the distribution of the
variables by putting them into similar categories. The analysis of frequencies has been used in
this study to determine the level of violence prevalence among males and female victims in
England and Wales. Analysis of frequencies was also used to study the number of the
respondents whose vehicles had been stolen away without permission during the violence.
A t-test was used in this report to compare means (Taeger, et al., 2014). The t-test is suitable for
comparing means since it is a technique that is applied when the analysis involves investigating
any significant difference in the average numbers of the variables. Another t-test was conducted
to determine whether there was any significant difference in the number of times males and
female respondents attended a nightclub in the last month (Yang, et al., 2018).
Analysis of variance (ANOVA) test was conducted to investigate whether there is any significant
difference in the incidences of violent crimes among different age groups of the respondents
(Agung & Gusti, 2011). Analysis of variance test was the most accurate in this case because the
investigation involves the average numbers (Marmolejo-Ramos, et al., 2017).

Cross-tabulation is a method of outlining the quantitative relationships between the variables
(Haspelmath & Martin, 2014). Cross table in the results section provides the quantities of
different categories of variables based on a given single variable. A cross tabulation was done to
investigate how much of a problem people become when they are drunk. The second cross
tabulation was done to find out how much of a problem are people using or dealing drugs
(Tajedor & Javier, 2017).
A correlation analysis was done to investigate whether there is any association or relationship
between how much of a problem are people using or dealing drugs and how much of a problem
are people being drunk or rowdy. The correlation coefficient indicates the strength of association
between the two variables (Neeti & Neeti, 2014). The second correlation analysis was conducted
to determine whether there exists any association or relationship between how much of a
problem are teenagers hanging and how much of a problem is vandalism, graffiti etc.
Literature Review
There are several studies that have been conducted on the topic of terrorism and polarization of
the community. The studies applied different statistical methods to achieve their objectives. For
example, a study by (Chainey, et al., 2008)applied trend analysis to establish that there has been
an overall increase in Wales and England in the recent past. Moreover, the study applied
correlation analysis to determine the factors that had a greater influence on the incidences of
crime in England and Wales.
Another study by (Batalova, 2010) applied the use of frequency analysis and cross tabulation to
determine the distribution of incidences of criminal activities across gender and age. The study
revealed that increasing criminal activities are becoming more sophisticated and more organized

by the perpetrators of a wide range of ages.
Correlation analysis was also used by (Chainey, et al., 2008) to determine whether there are
factors that predominantly influence the level of crimes. The study revealed that there are several
cases of money-related crimes in England. Similarly, analysis of variance (ANOVA) was used
by the researchers to determine whether there was any significant difference in the ages of the
perpetrators of criminal offenses.
According to the frequency analysis of difference criminal offenses, there is a general
emergence of different types of criminal offenses. Some of the criminal offences with increased
prevalence in England and Wales are: There is continuous rise in the number of police recorded
offenses that involve knives and other sharp objects, there has been a continuous increase in the
number of homicides and the number of police recorded offenses involving the use of firearms
(Melissa & Joshua, 2012).
Graphical representation of previous records of criminal offenses revealed that there has been an
increase in the prevalence of criminal of offenses across the gender and across the individuals of
a wide range of age. The increase in the cases of criminal offenses in Wales and England may be
as a result of the measures taken by the governments to increase community safety (Fenoff,
2013)
Data analysis
Frequencies
Gender Frequencies
The results in Table 1 below outlines the distribution of the number of male and female victims
of violence in England and Wales. The results demonstrate that there were a total of 35420
respondents. The total number of those who gave their accurate gender is 23724. The total

number of those who did not provide their gender is 11696. Out of the total number of those who
accurately gave their gender, 11791 were male respondents while 11933 were female
respondents. The male respondents are 33.3% while the female respondents are 33.7%.
Frequencies
TABLE VARIABLE
ANALYSIS
FREQUENCY TABLE
1-Statistics
Adult number 2: Sex
N Valid 23724
Missing 11696
Adult number 2: Sex
Frequency Percent
Valid
Percent
Cumulative
Percent
Valid 1 Male 11791 33.3 49.7 49.7
2 Female 11933 33.7 50.3 100.0
Total 23724 67.0 100.0
Missing System 11696 33.0
Total 35420 100.0
Pie Chart
The fig below is a pie chart representing the gender frequency. The pie chart is produced to
outline the proportion of male and female respondents in the study (Kovtun & Khovostenko,
2011). Observing the proportion of the males and females demonstrate that the number of female
and male respondents are almost equal as revealed by the frequency table above. The pie chart
demonstrates that the sample is well represented and unbiased.

Frequencies
VARIABLE
FREQUENCY
ANALYSIS TABLE 2-
Statistics
Adult number 2: Sex
N Valid 23724
Missing 11696
Adult number 2: Sex
Frequency Percent
Valid
Percent
Cumulative
Percent
Valid 1 Male 11791 33.3 49.7 49.7
2 Female 11933 33.7 50.3 100.0
Total 23724 67.0 100.0
Missing System 11696 33.0
Total 35420 100.0

Title of the table contains variables labels. The first column of the table list. The frequency table
above shows the number of each category of the respondents who had the opinion that the cases
of local crime have increased recently. The results reveal that there were 11933 representing
33.7% of the total sample of female respondents and 11791 representing 33.3% of the total
respondents. The rest of the 33% did not give their opinion. Therefore, it is clear that both male
and females equally have the opinion that cases of crime have increased recently.
T.TEST ANALYSIS TABLE
A t-test was used in this report to compare means (Martin, et al., 2012). The t-test is suitable for
comparing means since it is a technique that is applied when the analysis involves investigating
any significant difference in the average numbers of the variables. In this scenario, the interest is
to determine whether there is any significant difference in the average ages of the male and
female respondents.

The number of males in the group of respondents is 1255 while the number of females is 10371.
The mean age of the male respondents is 41.31 while the mean age of the female respondents is
50.20. The standard deviation of ages of the male respondents is 17.46 while the standard
deviation of the ages of the female respondents is 16.887. The standard error of the ages of the
male respondents is 0.493 while the standard error of the ages of the female respondents is 0.160.
T.TEST ANALYSIS TABLE 1-Group Statistics
Adult number 2:
Sex N Mean
Std.
Deviation
Std. Error
Mean
Adult number 2:
Age
1 Male 1255 41.31 17.464 .493
2 Female 10371 50.20 16.302 .160
Independent Samples Test
Levene's Test
for Equality of
Variances t-test for Equality of Means
F Sig. t df
Sig.
(2-
tailed)
Mean
Differ
ence
Std.
Error
Differ
ence
95%
Confidence
Interval of the
Difference
Lower Upper
Adult
number
2: Age
Equal
variances
assumed
23.421 .000 -
18.1
20
116
24
.000 -8.898 .491 -9.861 -7.936
Equal
variances
not assumed
-
17.1
69
153
0.34
9
.000 -8.898 .518 -9.915 -7.882
An independent t-test was conducted to investigate whether there is any significant difference in
the average number of males and females with trust in the police (Amiri, et al., 2014). The
results reveal that the p-value is 0.00. The p-value is less than the significance value. Therefore,

it is clear that there is indeed a significant difference in the average number of males and females
with trust in the police. Therefore, it is clearly demonstrated here that both the male and female
respondents equally have no trust in the police.
T-Test
The independent sample t-test was conducted to investigate whether there is any significant
difference in the number of time each of the respondents had visited a nightclub. The test was
done in two dimensions; assuming that the age of the male and female respondents had equal
variances as well as assuming that they had unequal variances. In both cases, the probability
value is similar (0.01). The test was a two-tailed test, meaning that the level of significance is
0.025. Therefore, the probability value is less than the level of significance.
T.TEST TABLE 2 ANALYSIS -Group Statistics
Adult number 2:
Sex N Mean
Std.
Deviation
Std. Error
Mean
How often have you
visited a nightclub in
the last month
1 Male 1274 1.26 .583 .016
2 Female 10417 1.06 .286 .003
Independent Samples Test
Levene's Test
for Equality of
Variances t-test for Equality of Means
F Sig. t df
Sig.
(2-
tailed)
Mean
Differ
ence
Std.
Error
Differ
ence
95%
Confidence
Interval of the
Difference
Lower Upper
How often
have you
visited a
Equal
variances
assumed
1258.
736
.000 19.
954
116
89
.000 .196 .010 .177 .216

nightclub in
the last
month
Equal
variances
not
assumed
11.
839
134
8.73
8
.000 .196 .017 .164 .229
The tables above represent the result of a t-test that was conducted to investigate whether there is
any significant difference in the average number of males and females with the opinion that the
number of crimes in England and Wales has increased in the recent years. The results reveal that
the t value (t=12.320) and the p-value 0.00. The p-value is clearly less than the level of
significance (0.05). Therefore, it is prudent to conclude that indeed there is a significant
difference in the average number of males and females with the opinion that the number of
crimes in England and Wales has increased in the recent years.
Oneway Analysis of Variance (ANOVA)
Analysis of variance (ANOVA) test was conducted to investigate whether there is any significant
difference in the incidences of violent crimes among different age groups of the respondents.
Analysis of variance test was the most accurate in this case because the investigation involves
the average numbers (Akbari, et al., 2015). The probability value of the test results is 0.00. This
probability value is less than the level of significance (0.025).
ONE WAY ANOVA TABLE 1 ANALYSIS -Descriptives
Adult number 1 (respondent): Sex
N Mean
Std.
Deviation
Std.
Error
95% Confidence
Interval for Mean
Minim
um
Maxim
um
Lower
Bound
Upper
Bound
16 107 1.00 .000 .000 1.00 1.00 1 1
17 134 1.00 .000 .000 1.00 1.00 1 1
18 131 1.00 .000 .000 1.00 1.00 1 1
19 120 1.00 .000 .000 1.00 1.00 1 1
20 137 1.00 .000 .000 1.00 1.00 1 1
21 132 1.00 .000 .000 1.00 1.00 1 1

22 146 1.00 .000 .000 1.00 1.00 1 1
23 149 1.00 .000 .000 1.00 1.00 1 1
24 169 1.00 .000 .000 1.00 1.00 1 1
25 170 1.00 .000 .000 1.00 1.00 1 1
26 180 1.00 .000 .000 1.00 1.00 1 1
27 241 1.00 .000 .000 1.00 1.00 1 1
28 226 1.00 .000 .000 1.00 1.00 1 1
29 210 1.00 .000 .000 1.00 1.00 1 1
30 240 1.00 .000 .000 1.00 1.00 1 1
31 220 1.00 .000 .000 1.00 1.00 1 1
32 241 1.00 .000 .000 1.00 1.00 1 1
33 261 1.00 .000 .000 1.00 1.00 1 1
34 269 1.00 .000 .000 1.00 1.00 1 1
35 254 1.00 .000 .000 1.00 1.00 1 1
36 276 1.00 .000 .000 1.00 1.00 1 1
37 274 1.00 .000 .000 1.00 1.00 1 1
38 245 1.00 .000 .000 1.00 1.00 1 1
39 260 1.00 .000 .000 1.00 1.00 1 1
40 255 1.00 .000 .000 1.00 1.00 1 1
41 241 1.00 .000 .000 1.00 1.00 1 1
42 274 1.00 .000 .000 1.00 1.00 1 1
43 283 1.00 .000 .000 1.00 1.00 1 1
44 314 1.00 .000 .000 1.00 1.00 1 1
45 299 1.00 .000 .000 1.00 1.00 1 1
46 302 1.00 .000 .000 1.00 1.00 1 1
47 302 1.00 .000 .000 1.00 1.00 1 1
48 275 1.00 .000 .000 1.00 1.00 1 1
49 275 1.00 .000 .000 1.00 1.00 1 1
50 292 1.00 .000 .000 1.00 1.00 1 1
51 270 1.00 .000 .000 1.00 1.00 1 1
52 285 1.00 .000 .000 1.00 1.00 1 1
53 326 1.00 .000 .000 1.00 1.00 1 1
54 297 1.00 .000 .000 1.00 1.00 1 1
55 268 1.00 .000 .000 1.00 1.00 1 1
56 286 1.00 .000 .000 1.00 1.00 1 1
57 239 1.00 .000 .000 1.00 1.00 1 1
58 260 1.00 .000 .000 1.00 1.00 1 1
59 252 1.00 .000 .000 1.00 1.00 1 1

60 275 1.00 .000 .000 1.00 1.00 1 1
61 271 1.00 .000 .000 1.00 1.00 1 1
62 280 1.00 .000 .000 1.00 1.00 1 1
63 289 1.00 .000 .000 1.00 1.00 1 1
64 286 1.00 .000 .000 1.00 1.00 1 1
65 294 1.00 .000 .000 1.00 1.00 1 1
66 267 1.00 .000 .000 1.00 1.00 1 1
67 293 1.00 .000 .000 1.00 1.00 1 1
68 285 1.00 .000 .000 1.00 1.00 1 1
69 334 1.00 .000 .000 1.00 1.00 1 1
70 275 1.00 .000 .000 1.00 1.00 1 1
71 250 1.00 .000 .000 1.00 1.00 1 1
72 278 1.00 .000 .000 1.00 1.00 1 1
73 222 1.00 .000 .000 1.00 1.00 1 1
74 200 1.00 .000 .000 1.00 1.00 1 1
75 178 1.00 .000 .000 1.00 1.00 1 1
76 186 1.00 .000 .000 1.00 1.00 1 1
77 178 1.00 .000 .000 1.00 1.00 1 1
78 173 1.00 .000 .000 1.00 1.00 1 1
79 147 1.00 .000 .000 1.00 1.00 1 1
80 162 1.00 .000 .000 1.00 1.00 1 1
81 128 1.00 .000 .000 1.00 1.00 1 1
82 127 1.00 .000 .000 1.00 1.00 1 1
83 114 1.00 .000 .000 1.00 1.00 1 1
84 94 1.00 .000 .000 1.00 1.00 1 1
85 95 1.00 .000 .000 1.00 1.00 1 1
86 65 1.00 .000 .000 1.00 1.00 1 1
87 55 1.00 .000 .000 1.00 1.00 1 1
88 35 1.00 .000 .000 1.00 1.00 1 1
89 40 1.00 .000 .000 1.00 1.00 1 1
90 44 1.00 .000 .000 1.00 1.00 1 1
91 20 1.00 .000 .000 1.00 1.00 1 1
92 14 1.00 .000 .000 1.00 1.00 1 1
93 20 1.00 .000 .000 1.00 1.00 1 1
94 8 1.00 .000 .000 1.00 1.00 1 1
95 4 1.00 .000 .000 1.00 1.00 1 1
96 6 1.00 .000 .000 1.00 1.00 1 1
97 2 1.00 .000 .000 1.00 1.00 1 1

99 2 1.00 .000 .000 1.00 1.00 1 1
100 100 or
over
1 1.00 . . . . 1 1
Total 16384 1.00 .000 .000 1.00 1.00 1 1
Analysis of Variance (ANOVA)
Adult number 1 (respondent): Sex
Sum of
Squares Df Mean Square F Sig.
Between
Groups
.000 83 .000 . .
Within Groups .000 16300 .000
Total .000 16383
One-way
ONE WAY ANOVA TABLE 2 ANALYSIS -Descriptive
Adult number 2: Sex
N Mean
Std.
Deviation
Std.
Error
95% Confidence Interval
for Mean
Minimu
m
Maximu
m
Lower
Bound
Upper
Bound
16 42 1.40 .497 .077 1.25 1.56 1 2
17 35 1.34 .482 .081 1.18 1.51 1 2
18 51 1.39 .493 .069 1.25 1.53 1 2
19 53 1.32 .471 .065 1.19 1.45 1 2
20 81 1.49 .503 .056 1.38 1.61 1 2
21 100 1.57 .498 .050 1.47 1.67 1 2
22 93 1.61 .490 .051 1.51 1.71 1 2
23 114 1.72 .451 .042 1.64 1.80 1 2
24 110 1.76 .427 .041 1.68 1.84 1 2
25 161 1.75 .437 .034 1.68 1.81 1 2
26 173 1.83 .380 .029 1.77 1.88 1 2
27 185 1.88 .325 .024 1.83 1.93 1 2
28 211 1.87 .340 .023 1.82 1.91 1 2
29 193 1.89 .312 .022 1.85 1.94 1 2
30 228 1.86 .348 .023 1.81 1.91 1 2

31 194 1.90 .298 .021 1.86 1.94 1 2
32 214 1.93 .248 .017 1.90 1.97 1 2
33 216 1.94 .247 .017 1.90 1.97 1 2
34 221 1.95 .218 .015 1.92 1.98 1 2
35 225 1.93 .258 .017 1.90 1.96 1 2
36 215 1.95 .211 .014 1.93 1.98 1 2
37 210 1.96 .203 .014 1.93 1.98 1 2
38 210 1.90 .294 .020 1.86 1.94 1 2
39 218 1.92 .269 .018 1.89 1.96 1 2
40 218 1.93 .261 .018 1.89 1.96 1 2
41 217 1.93 .254 .017 1.90 1.96 1 2
42 220 1.94 .245 .016 1.90 1.97 1 2
43 227 1.95 .215 .014 1.92 1.98 1 2
44 224 1.91 .292 .020 1.87 1.94 1 2
45 246 1.91 .286 .018 1.87 1.95 1 2
46 217 1.91 .290 .020 1.87 1.95 1 2
47 201 1.88 .325 .023 1.84 1.93 1 2
48 195 1.91 .290 .021 1.87 1.95 1 2
49 222 1.89 .317 .021 1.85 1.93 1 2
50 223 1.83 .377 .025 1.78 1.88 1 2
51 240 1.84 .366 .024 1.80 1.89 1 2
52 226 1.89 .309 .021 1.85 1.93 1 2
53 260 1.87 .338 .021 1.83 1.91 1 2
54 226 1.84 .371 .025 1.79 1.88 1 2
55 220 1.82 .383 .026 1.77 1.87 1 2
56 180 1.89 .315 .023 1.84 1.94 1 2
57 200 1.89 .314 .022 1.85 1.93 1 2
58 226 1.91 .285 .019 1.87 1.95 1 2
59 197 1.93 .258 .018 1.89 1.97 1 2
60 238 1.89 .307 .020 1.86 1.93 1 2
61 159 1.95 .219 .017 1.92 1.98 1 2
62 201 1.93 .263 .019 1.89 1.96 1 2
63 199 1.94 .229 .016 1.91 1.98 1 2
64 184 1.92 .266 .020 1.89 1.96 1 2
65 196 1.92 .267 .019 1.89 1.96 1 2
66 178 1.98 .129 .010 1.96 2.00 1 2
67 199 1.96 .185 .013 1.94 1.99 1 2
68 184 1.97 .163 .012 1.95 2.00 1 2

69 199 1.94 .229 .016 1.91 1.98 1 2
70 193 1.96 .187 .013 1.94 1.99 1 2
71 143 1.97 .165 .014 1.94 2.00 1 2
72 158 1.95 .220 .017 1.91 1.98 1 2
73 148 1.98 .141 .012 1.96 2.00 1 2
74 121 1.95 .218 .020 1.91 1.99 1 2
75 108 1.97 .165 .016 1.94 2.00 1 2
76 95 1.93 .263 .027 1.87 1.98 1 2
77 90 2.00 .000 .000 2.00 2.00 2 2
78 80 1.94 .244 .027 1.88 1.99 1 2
79 72 1.94 .231 .027 1.89 2.00 1 2
80 73 1.95 .229 .027 1.89 2.00 1 2
81 53 1.98 .137 .019 1.94 2.02 1 2
82 55 2.00 .000 .000 2.00 2.00 2 2
83 36 1.92 .280 .047 1.82 2.01 1 2
84 27 1.89 .320 .062 1.76 2.02 1 2
85 17 1.88 .332 .081 1.71 2.05 1 2
86 23 2.00 .000 .000 2.00 2.00 2 2
87 13 1.92 .277 .077 1.76 2.09 1 2
88 13 1.54 .519 .144 1.22 1.85 1 2
89 7 1.86 .378 .143 1.51 2.21 1 2
90 11 1.82 .405 .122 1.55 2.09 1 2
91 4 2.00 .000 .000 2.00 2.00 2 2
92 3 2.00 .000 .000 2.00 2.00 2 2
93 2 2.00 .000 .000 2.00 2.00 2 2
94 4 1.75 .500 .250 .95 2.55 1 2
96 1 2.00 . . . . 2 2
97 1 1.00 . . . . 1 1
Total 11626 1.89 .310 .003 1.89 1.90 1 2
ANOVA
Adult number 2: Sex
Sum of
Squares Df Mean Square F Sig.
Between
Groups
116.880 80 1.461 16.823 .000

Within Groups 1002.646 11545 .087
Total 1119.526 11625
Crosstabs
Crosstablesprovide the quantities of different categories of variables based on a given single
variable. The cross table below represents the number of incidences in the last 12 months that the
respondents have been a problem as a result of being drunk or rowdy.
CROSSTABS ANALYSIS TABLE 1-Case Processing Summary
Cases
Valid Missing Total
N Percent N Percent N Percent
How much of a
problem are people
being drunk or rowdy *
Adult number 1
(respondent): Sex
4297 26.1% 12140 73.9% 16437 100.0%
Chi-Square Tests
Value
Pearson Chi-
Square
.a
N of Valid Cases 4297
a. No statistics are computed
because Adult number 1
(respondent): Sex is a
constant.

Symmetric Measures
Value
Nominal by
Nominal
Phi .a
N of Valid Cases 4297
a. No statistics are computed because
Adult number 1 (respondent): Sex is a
constant.
crosstabs
CROSSTABS ANALYSIS TABLE 2 -Case Processing Summary
Cases
Valid Missing Total
N Percent N Percent N Percent
How much of a
problem are people
using or dealing drugs
* Adult number 1
(respondent): Sex
4139 25.2% 12298 74.8% 16437 100.0%
Chi-Square Tests
Value
Pearson Chi-
Square
.a
N of Valid Cases 4139

a. No statistics are computed
because Adult number 1
(respondent): Sex is a
constant.
Symmetric Measures
Value
Nominal by
Nominal
Phi .a
N of Valid Cases 4139
Correlations
A correlation analysis was done to investigate whether there is any association or relationship
between how worried one is about being attacked by a stranger and how one is about being
attacked because of their skin color, ethnic origin or religion. The correlation coefficient
indicates the strength of association between the two variables.
/VARIABLES=druguse drunk
/PRINT=TWOTAIL NOSIG
/MISSING=PAIRWISE.
Correlations
CORRELATIONS ANALYSIS TABLE 1 -Correlations
How much of
a problem are
people using
or dealing
drugs
How much of
a problem are
people being
drunk or
rowdy
How much of a
problem are people
using or dealing drugs
Pearson
Correlation
1 .581**
Sig. (2-tailed) .000
N 4139 4130

How much of a
problem are people
being drunk or rowdy
Pearson
Correlation
.581** 1
Sig. (2-tailed) .000
N 4130 4297
**. Correlation is significant at the 0.01 level (2-tailed).
Correlations
A correlation analysis was conducted to investigate whether there is any significant association
between how much of a problem are teenagers hanging around and how much of a problems
vandalism, graffiti etc. The table below outline the results of the test. The table below reveals
that the correlation coefficient between the variables is 0.496. The correlation coefficient of
0.496 is a weak positive correlation coefficient. A positive correlation coefficient demonstrates
that as the problems caused by teenagers hanging around increases, the problems of vandalism,
graffitis etc also increases.
CORRELATIONS ANALYSIS TABLE 2 -Correlations
How much of
a problem are
teenagers
hanging
around
How much of
a problem is
vandalism,
graffiti etc?
How much of a
problem are teenagers
hanging around
Pearson
Correlation
1 .496**
Sig. (2-tailed) .000
N 4316 4307
How much of a
problem is vandalism,
graffiti etc?
Pearson
Correlation
.496** 1
Sig. (2-tailed) .000
N 4307 4310

Conclusion
The results in the analysis chapter demonstrate that there were a total of 35420 respondents. The
total number of respondents who gave their gender is 23724. The total number of respondents
who did not indicate their gender are 11696. Out of the total number of those who accurately
indicated their gender, 11791 were male respondents while 11933 were female respondents. The
male respondents were 33.3% while the female respondents were 33.7%. From the results, it is
clear that there were more female respondents than male respondents (Agung & Gusti, 2011).
However, the difference in a number of the male and female respondents are not very big
(Chainey, et al., 2008). Therefore, the sample had a proper representation of both genders. The
sample was properly collected and it was unbiased. An unbiased sample is a sample that does not
over-represent or under-represent a given variable or groups of the variable (Taeger, et al., 2014).
A t-test was used to determine whether there was any significant difference in the ages of the
male and the female respondents. A representative samples of opinion of male and female in
England and whales were asked what has happened to crime in your local area over the past few
years .in average, these respondent hold that less than two third are incarcerated (means
=1.26 .however, the result of the T-test shows that there is a statistically significant difference
between gender s in this view.
In average men tend to think that more rapist is imprisoned (mean=1.26) than female is
(mean=1.26 There is an obvious lack of trust of the population that rape is treated as a serious
crime wherein average respondents think that one-third of the rapist avoids prison sentencing. It
probably does not come as a surprise those women 1.06 even less trusting in the criminal justice

system when rape is in question
The number of males in the group of respondents is 1255 while the number of females is 10371.
The mean age of the male respondents is 41.31 while the mean age of the female respondents is
50.20. The standard deviation of ages of the male respondents is 17.46 while the standard
deviation of the ages of the female respondents is 16.302. The standard error of the ages of the
male respondents is 0.493 while the standard error of the ages of the female respondents is 0.160.
The independent sample t-test was conducted to investigate whether there is any significant
difference in the mean ages of the male and the female respondents (Neeti & Neeti, 2014).
The test was done in two dimensions; assuming that the age of the male and female respondents
had equal variances as well as assuming that they had unequal variances. In both cases, the
probability value is 0.01. The test was a two-tailed test, meaning that our level of significance is
0.025. Therefore, the probability value is less than the level of significance. Therefore, this is a
clear indication that there was no significant difference in the average ages of the male and
female ages. The study had a sample of respondents of relatively equal ages.
The second t-test was conducted to investigate whether there is any significant difference in the
number of occasions that the males and the females visited a nightclub. The probability value is
0.00. This probability value is less than the significance value which is 0.025. Therefore, it is
clear that there was a significant difference in the number of occasions that the males and the
females visited a nightclub. We can argue that perhaps males go to the nightclub more frequently
than the females (Tajedor & Javier, 2017).
Analysis of variance (ANOVA) test was conducted to investigate whether there is any significant
difference in the incidences of violent crimes among different age groups of the respondents.

Analysis of variance test was the most accurate in this case because the investigation involves
the average numbers. The results indicate that the probability value was 0.00. This probability
value is less than the level of significance which is 0.025. Therefore, we conclude that there was
indeed a significant difference in the average number of incidences of violent crimes among
different age groups of the respondents.
The second analysis of variance (ANOVA) test was done to investigate whether there is any
significant difference in the averages of how an individual is worried about being attacked
because of skin color. The results clearly indicate that the probability value is 0.00. The
probability value is less than the level of significance (0.025). Therefore, there is a significant
difference in the averages of how an individual is worried about being attacked because of skin
color.
The other analysis that was done is the cross-tabulation analysis. Cross table in the results section
provides the quantities of different categories of variables based on a given single variable. The
cross table below represents the number of incidences in the last 12 months with age motivated
personal crimes. The table demonstrates that the number of violence against women in the last 12
months is much greater than the number of violence against men in the last 12 months.
Therefore, we can see that women are more vulnerable to violent offenses than their male
counterparts. The females are considered an an easy target by the perpetrators because they are
not strong to defend themselves.
The second cross tabulation was done to find out the level of trust that the respondents have
towards the police. The results indicate that majority of the respondents gave a positive response
(1432). The positive responses represented 57.2 % while the negative responses gave 42.8 %.
Therefore, we can say that generally, the majority of the people believe that the police can help

in restoring and maintaining peace and to help in reducing the violence in England and Wales.
A correlation analysis was done to investigate whether there is any association or relationship
between how worried one is about being attacked by a stranger and how much of a problem are
people using or dealing drugs and how much of a problem are people being drunk or rowdy. The
correlation coefficient indicates the strength of association between the two variables. The
correlation coefficient between how worried one is about being attacked by a stranger and how
much of a problem are people using or dealing drugs and how much of a problem are people
being drunk or rowdy is 0.581. This is a strong positive correlation coefficient (Martin, et al.,
2012). This coefficient correlation indicates that the more problematic people become as a result
of using or dealing drugs the more problematic people are or become as a result of being drunk
or rowdy (Yang, et al., 2018).
The second correlation analysis was conducted to determine whether there exists any association
or relationship between how much of a problem are teenagers hanging around and how much of
problem is vandalism, graffiti etc. The correlation coefficient between how much of a problem
are teenagers and the problems caused by vandalism, graffiti etc. is 0.496. This is a weak positive
correlation. This correlation coefficient demonstrates that as the problems caused by teenagers
hanging around increases, the problems caused by vandalism, graffiti also increases. Therefore,
we can argue that crimes such as vandalism, graffiti and the rest are promoted by teenagers who
hang around with no job to do.

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Appendix
Appendix 1: Gender Frequency case processing
TABLE 1-Statistics
Adult number 2: Sex
N Valid 23724
Missing 11696
Appendix 2: Vehicle stolen or not case processing
TABLE 2- Statistics
If vehicle stolen or driven away without permission
N Valid 14602
Missing 4381
Appendix 3: ANOVA Test one Statistics
TABLE 8-Descriptives
Age motivated household crime 50-53,55-58,60-65,71,72,80-86, incidence in last 12 months
N Mea
n
Std.
Deviatio
n
Std.
Error
95%
Confidence
Interval for
Mean
Minimu
m
Maximu
m
Lowe
r
Boun
d
Upper
Bound
0 3539
2
1.16 40.814 .217 .73 1.58 0 3000
1000 21 47.6
2
218.218 47.61
9
-51.71 146.9
5
0 1000
2000 4 .00 .000 .000 .00 .00 0 0
3000 2 .00 .000 .000 .00 .00 0 0
4000 1 .00 . . . . 0 0
Tota
l
3542
0
1.19 41.141 .219 .76 1.61 0 3000

Appendix 4: Post Hoc test Statistics
*. The mean difference is significant at the 0.05 level.
Means
TABLE 12-Case Processing Summary
Cases
Included Excluded Total
N Percent N Percent N Percent
How worried about
being attacked because
of skin color - recoded
* Ethnic Group (5
categories)
8487 24.0% 26933 76.0% 35420 100.0%
TABLE 13
How worried about being attacked because of skin color - recoded
Ethnic Group (5 categories) Mean N Std. Deviation
1 White .11 7587 .384
2 Mixed .26 76 .574
3 Asian or Asian British .54 434 .765
4 Black or Black British .50 260 .758
5 Chinese or Other .39 130 .676
Total .15 8487 .452
Frequencies
TABLE 14-Statistics
Age Categories
N Valid 35420
Missing 0
Appendix 5: Cross Tabulation Case Processing Summary
TABLE 15- Case Processing Summary
Cases

Valid Missing Total
N Percen
t
N Percen
t
N Percen
t
Gender motivated personal crime
11,12,13,21,32,33,41,42,43,44,45,67,
73, no of incidents in last 12 months
* Age motivated personal crime
11,12,13,21,32,33,41,42,43,44,45,67,
73, no of incidents in last 12 months
3542
0
100.0
%
0 0.0% 3542
0
100.0
%
Crosstabs
TABLE 19-Case Processing Summary
Cases
Valid Missing Total
N Percent N Percent N Percent
In general how much
do you trust the police
as an organisation *
What has affected trust
in the police as an
organisation - Positive
personal experience
with the police
9237 26.1% 26183 73.9% 35420 100.0%
TABLE 18-Symmetric Measures
Value Asymptotic
Standard
Errora
Approximate
Tb
Approximate
Significance
Nominal by
Nominal
Phi .850 .000
Cramer's V .380 .000
Ordinal by
Ordinal
Kendall's
tau-b
.249 .068 2.994 .003
N of Valid Cases 35420
a. Not assuming the null hypothesis.

b. Using the asymptotic standard error assuming the null hypothesis.
TABLE 17-Chi-Square Tests
Value df Asymptotic
Significance (2-
sided)
Pearson Chi-Square 25595.917a 25 .000
Likelihood Ratio 105.332 25 .000
Linear-by-Linear Association 4112.684 1 .000
N of Valid Cases 35420
a. 33 cells (91.7%) have expected count less than 5. The minimum expected count is .00.
Cross Tabulation
How much of a problem are people using or dealing drugs * Adult number 1
(respondent): Sex Crosstabulation
Adult
number 1
(respondent)
: Sex
Total1 Male
How much of a
problem are people
using or dealing drugs
1 Very big problem Count 279 279
% within Adult
number 1
(respondent): Sex
6.7% 6.7%
Adjusted Residual .
2 Fairly big problem Count 533 533
% within Adult
number 1
(respondent): Sex
12.9% 12.9%
Adjusted Residual .
3 Not a very big
problem
Count 1180 1180
% within Adult
number 1
(respondent): Sex
28.5% 28.5%
Adjusted Residual .
4 Not a problem at Count 2147 2147

all % within Adult
number 1
(respondent): Sex
51.9% 51.9%
Adjusted Residual .
Total Count 4139 4139
% within Adult
number 1
(respondent): Sex
100.0% 100.0%
How much of a problem are people being drunk or rowdy * Adult number 1
(respondent): Sex Crosstabulation
Adult
number 1
(respondent)
: Sex
Total1 Male
How much of a
problem are people
being drunk or rowdy
1 Very big problem Count 129 129
% within Adult
number 1
(respondent): Sex
3.0% 3.0%
Adjusted Residual .
2 Fairly big problem Count 443 443
% within Adult
number 1
(respondent): Sex
10.3% 10.3%
Adjusted Residual .
3 Not a very big
problem
Count 1743 1743
% within Adult
number 1
(respondent): Sex
40.6% 40.6%
Adjusted Residual .
4 Not a problem at
all
Count 1982 1982
% within Adult
number 1
(respondent): Sex
46.1% 46.1%
Adjusted Residual .
Total Count 4297 4297

% within Adult
number 1
(respondent): Sex
100.0% 100.0%