Data Analysis Report

This data analysis report examines the relationship between crime statistics and population. It analyzes the impact of population on murder, rape, and robbery cases using descriptive and inferential statistics. The report concludes that murder cases may increase with population growth, while rape and robbery cases are expected to remain stable. Recommendations for stricter rules to reduce crime rates are provided.

DATA ANALYSIS REPOERT

TABLE OF CONTENTS
INTRODUCTION...........................................................................................................................1
Statistical analysis............................................................................................................................1
Part 1: Descriptive statistics........................................................................................................1
Part 2: Inferential statistics..........................................................................................................2
Murder and population......................................................................................................2
Rape and population..........................................................................................................4
Robbery and population.....................................................................................................6
CONCLUSION................................................................................................................................7
REFERENCES................................................................................................................................9

INTRODUCTION
In the present research study data related to crime is analysed by using descriptive and inferential statistics. Crime data is analysed
because in the current time period varied sort of crimes are increasing and it is very important to identify the crime that is increasing at
rapid pace so that action can be taken to control it. In current research by using tools murder, rape and robbery related data is analysed.
Through data analysis main aim is to identify crime type which may increase at rapid pace in the upcoming time period and in this
regard entire work is carried out.
Statistical analysis
Part 1: Descriptive statistics
Descriptive statistics
MURDER RAPE ROBBERY population
Mean 4.68463 Mean
26.3249
4 Mean
112.447
7 Mean 100732.9
Standard Error
0.41671
6 Standard Error
1.41623
4 Standard Error
11.8984
2 Standard Error 5761.725
Median 0 Median 5 Median 4 Median 25812.5
Mode 0 Mode 0 Mode 0 Mode 11961
Standard Deviation
23.3361
1 Standard Deviation 79.3091 Standard Deviation
666.311
4 Standard Deviation 322656.6
Sample Variance 544.573 Sample Variance 6289.93 Sample Variance 443970. Sample Variance 1.04E+1
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9 3 9 1
Kurtosis
308.574
4 Kurtosis
161.242
3 Kurtosis
352.767
2 Kurtosis 333.6485
Skewness 15.0935 Skewness
9.87648
1 Skewness
16.0341
2 Skewness 14.12425
Range 600 Range 1976 Range 18923 Range
1001697
8
Minimum 0 Minimum 0 Minimum 0 Minimum 90
Maximum 600 Maximum 1976 Maximum 18923 Maximum
1001706
8
Sum 14691 Sum 82555 Sum 352636 Sum
3.16E+0
8
Count 3136 Count 3136 Count 3136 Count 3136
95% CI lower
bound
95% CI upper
bound
3.87
5.50
95% CI lower
bound
95% CI upper
bound
23.55
29.10
95% CI lower
bound
95% CI upper
bound
89.12
135.78
95% CI lower
bound
95% CI upper
bound
89435
112030
On basis of table above it can be observed that statistics value for the murder is (M= 4.68, SD=23.33). This indicate that on an
average 5 cases of murder are observed in most of country and this rate deviate at standard deviation of 23.33 which is low. In case of
rape statistics are (M= 26.32, SD=1.41) which reflect that on an average 26 cases of rape are observed in counties and this rate does
not even deviate as standard deviation value is just 1.41. In case of Robbery value of statistic is (M= 112.47, SD=666.33) which
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means that on an average 112 cases of Robbery are observed in each county. However, this deviate at high rate as value of standard
deviation is 666.33. In respect to population statistic values are (M= 100732, SD=322656) which reflect that on an average population
of statistic remain 100732 and its value deviate at 322656. Overall, it can be said that robbery cases are very high across counties
relative to rape and murder. Rape comes on number 2 and is far behind robbery in respect to mean value. This reflect that
unemployment or earning of less amount of money to continue life may be reasons behind such a higher case of robbery.
Part 2: Inferential statistics
Murder and population
H0: There is no significant impact of increase in population on number of murder cases.
H1: There is significant impact of increase in population on number of murder cases.
Model Summary
Model R R Square Adjusted R
Square
Std. Error of
the Estimate
1 .838a .702 .702 12.744
a. Predictors: (Constant), population
ANOVAa
Model Sum of
Squares
df Mean
Square
F Sig.
1
Regression 1198262.630 1 1198262.630 7378.249 .000b
Residual 508976.469 3134 162.405
Total 1707239.099 3135
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a. Dependent Variable: MURDER
b. Predictors: (Constant), population
Coefficientsa
Model Unstandardized
Coefficients
Standardized
Coefficients
t Sig.
B Std. Error Beta
1 (Constant) -1.419 .238 -5.952 .000
population 6.059E-005 .000 .838 85.897 .000
a. Dependent Variable: MURDER
Interpretation
Value of R square 0.70 indicate that model is effectively explaining relationship between dependent and independent variable.
Value of level of significance is 0.00<0.05 which indicate that there is significant impact of the population on the murder cases.
Alternative hypothesis accepted. Beta coefficient is 6.06 which reflect that with increase in population in number cases of murder will
increase by 6. Thus, it can be said that with fast increase in population cases of murder will also increase. This happened because in
county multiple religion people belong to different nation live together and discrimination happened (Oxburgh and et.al., 2015).
Hence, many time fights between different group convert into murder. CI level for murder is (3.87 LB, 5.50 UB and Mean is 4.68),
standard deviation value is low which reflect that in future time period cases of murder will not increase at rapid pace.
Rape and population
H0: There is no significant impact of population increase on cases of rape.
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H1: There is significant impact of population increase on cases of rape.
Model Summary
Model R R Square Adjusted R
Square
Std. Error of
the Estimate
1 .893a .797 .797 35.699
a. Predictors: (Constant), population
ANOVAa
Model Sum of
Squares
df Mean Square F Sig.
1
Regression 15724943.37
3 1 15724943.37
3 12339.012 .000b
Residual 3993996.517 3134 1274.409
Total 19718939.89
0 3135
a. Dependent Variable: RAPE
b. Predictors: (Constant), population
Coefficients
Model Unstandardized
Coefficients
Standardized
Coefficients
t Sig.
B Std. Error Beta
1 (Constant) 4.214 .668 6.310 .000
population .000 .000 .893 111.081 .000
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a. Dependent Variable: RAPE
Interpretation and discussion
Value of level of significance is 0.00<0.05 which reflect that with change in population significance change comes in the case
of rape. Alternative hypothesis accepted. R square value is 0.79 which reflect model is effectively explaining relationship between
variables. More viewing of porn videos and materialism in movies are the reasons behind rape. Beta value is 0.00 which reflect that
with change in population no increase will be observed in cases of rape. In case of rape statistic value is (23.55, 29.10 UB and Mean is
26.32) and standard deviation value here also is very low. It is expected that in upcoming time period rape statistics will remain same
as present.
Robbery and population
H0: There is no significant impact of change in population on cases of robbery.
H1: There is significant impact of change in population on cases of robbery.
Model Summary
Model R R Square Adjusted R
Square
Std. Error of
the Estimate
1 .898a .806 .806 293.165
a. Predictors: (Constant), population
ANOVAa
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Model Sum of
Squares
df Mean Square F Sig.
1
Regression 1122494540.
306 1 1122494540.
306 13060.486 .000b
Residual 269354277.1
17 3134 85945.845
Total 1391848817.
423 3135
a. Dependent Variable: ROBBERY
b. Predictors: (Constant), population
Coefficientsa
Model Unstandardized
Coefficients
Standardized
Coefficients
t Sig.
B Std. Error Beta
1 (Constant) -74.364 5.484 -13.559 .000
population .002 .000 .898 114.282 .000
a. Dependent Variable: ROBBERY
Interpretation and discussion
R square value is 0.80 which reflect that model is effectively explaining relationship between variables. Value of level of
significance is 0.00<0.05 which reflect that with change in independent variable huge change comes in dependent variable. Alternative
hypothesis accepted. Beta coefficient is 0.00 which means that with change in population not change will come in robbery cases. This
result is obtained because in the county large population is employed and due to this reason, they do not need to do robbery (Wells and
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et.al., 2016). Unemployment is not expected to increase even at moderate rate. Hence, no change is expected in robbery rate even
population get increased. In case of robbery is (89.12 LB, 135.78 UB and Mean is 112.45), It can be said that in case of robbery level
is wide as standard deviation is high. Hence, in case of robbery higher elevation can be observed.
CONCLUSION
On the basis of above discussion, it is concluded that with change in the population rape, murder and robbery number get
affected. However, results reflect that murder is one of crime whose number can increase with slight change in population. This
happened because in each county in each year number of new people comes that belong to Asia and Africa. These regions people are
completely different from each other in terms of culture, religion, belief, thinking and attitude and skin colour if both groups are
compared with each other or with European people. All these groups assume self as superior and other as inferior and due to this
reason clashes happened between people. Many times, such kind of clashes result in murder. Moreover, sometime due to family
reasons people comes in conflict and this lead to death of someone. Along with this, in college many gangs operate in group and
sometime clashes happened between them. Such kind of thing lead to murder of someone.
In case of rape and robbery mean value is high relative to other but beta value is low which lead to conclusion that even
population get increase both crime will remain in same state as seen in current time period. Thus, much importance is not given to
them. Beta value for murder is 6 which is sufficient to reflect that if population increase in county then cases of murder will increase at
rapid pace. In current time period it is in control but may rise at fast rate in upcoming years. Hence, it is recommended that strict rules
must be bring in respect to relevant crimes so that their growth rate can be reduced.
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REFERENCES
Books and Journals
Oxburgh, G. and et.al., 2015. Police officers’ perceptions of interviews in cases of sexual offences and murder involving children and
adult victims. Police practice and research. 16(1). pp.36-50.
Wells, W. and et.al., 2016. The characteristics and results of eyewitness identification procedures conducted during robbery
investigations in Houston, TX. Policing: An International Journal of Police Strategies & Management. 39(4). pp.601-619.
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