Canada’s Shift in Population Demographics Leads to a Decrease in Crime Rates

The study explores the impact of population demographics on crime rates in Canada. It analyzes the relationship between age, income, population size, and police deployment on crime rates. The study aims to understand the factors influencing the decline in crime rates in Canada.

Running head: POPULATION AND CRIMES RATES
1
Canada’s Shift in Population Demographics Leads to a Decrease in Crime Rates
Student Name
Institution

POPULATION AND CRIME RATES 2
1.0 Introduction
1.1 Purpose of the Study
The main purpose of the study is to determine of there exist any relationship between
demographical shift and crime rates in Canada. Demographic is the study of the composition of
population (Cyree & Morris, 2018). Population is characterized by size, age, gender, and income
of people in a population. The composition of population has effect on the social and economic
behavior of individual and thus likely to have an impact on crime rates in a country. Crime is an
extremely important area to focus on as it directly involves our wellbeing as Canadian citizens.
This report will focus on population demographical shifts as well as age and various other factors
to determine the cause of the decline. In addition, the report aims to find out the factors that
influence the decrease in crime rates to be able to predict present and future trends as a way of
ensuring the safety Canada residents.
1.2 Main Research Question
Does the population demographic have any impact on the rate of crime in Canada?
1.3 Research Questions
i. Does income of a population have on crime rates in Canada?
ii. What is the relationship between population size and crime rates in Canada?
iii. Is there a significant relationship between size and crime rates in Canada?
iv. Is there any relationship between number of police officers deployed in an area and
crime rates?
v. Which age group commits most crimes in Canada?
1.4 Sampling Technique

POPULATION AND CRIME RATES 3
The data used for analysis in the research study is secondary and was retrieved from ().
The data used is factual data from mid 1940s to 2018.
1.5 Hypothesis Statement
It is predicted that crimes in Canada are declining because of the shift in population
demographics, more specifically focusing in on the baby boomer’s generation and their affects
during various ages.
2.0 Analysis
This chapter will present data analysis of Canadian demographics and the crime rates in
Canada. The analysis will include mean, median, mode, variance, standard deviation, whisker
plot, correlation coefficient, linear regression, and graphical displays. The analysis of available
data is very important in determination whether demographics actually have effect on crime rates
in Canada. In addition, the analysis of effect age groups will assist in understanding why
generational shifts in population affect the amounts of crimes in certain years versus other
demographic factors.
2.1 Population Composition by Age

POPULATION AND CRIME RATES 4
According to the 2017 census, Canada population is approximately 36.63 million. The graph
above represents the influx in population, showing the age of the baby boomers in 2017. The
results show that from the ages of 40 – 70 there is a larger percent of people than in the other age
groups. This information is important as a visual that shows how this generation affects the
population and the age group they are a part of. This demonstrates that when this generation was
in their youth there was an abundance more of them, more people means a higher crime rate.

POPULATION AND CRIME RATES 5
19%
8%
13%61%
Population Growth by Age
Total Population
0-14
15-64
65+
Pie chart showing the populations growth by age in various age groups (65+, 15-64, 0-14, Total population).
The pie chart above represents just how greatly demographic shifts affect the population. The
results show that 61% of Canadas population is older than 65, while only 8% is aged 0-14. These
results once again demonstrate the shifts in demographics over the years and how majority of our
population is older than 65. This information is important to reiterate that when this generation
were in their youth, majority of the population would have been youths/youth adults and crime
rates would have increases.

POPULATION AND CRIME RATES 6
Drug offences
Criminal Code traffic offences
Other Criminal Code offences
Property crime
Violent crime
0
500
1000
1500
2000
2500
Offences By Age and Offence Type
Youth aged 12 to 17
Young adults aged 18
to 24
Older adults aged 25
and over
Offence Type
Rate per 100,000 Population
The above bar graph illustrates various crimes and the number of offences within certain age
groups. Figure 5 shows that young adults aged 18 to 24 had the highest rates for all of the
offences other than property crime. The second highest rates for number of crimes committed
were youths aged 12 to 17, and last having a significantly less number of offences, adults 25+.
This suggests that young adults are more likely to be accused of and commit crimes than adults
or young children. The median age for young adults is 21 and most offences occur at around this
age
2.2 Demographic studies

POPULATION AND CRIME RATES 7
1
5
9
13
17
21
25
29
33
37
41
45
49
53
0
500
1,000
1,500
2,000
2,500
3,000
3,500
4,000
4,500
5,000
Amount of Births in canada ('000)
Amount of Births in
thousands
The above histogram shows the number of births in Canada from 1940 to 1994. The number o
birth is increasing steadily from 1994 to 1964 then a slight decrease in the number of births from
1965 to 1988. From 1989, a steady increase in births is realized until 1994. Such increase in the
births could be as a result o improved health care and income increase. Improved health care and
income is an indicator of good economic status of a country/individual.
2.3 Measures of Central Tendency
Total Crimes
population
size GDP
Mean 8519.037037 28618476.41
79.8435658
3
Standard Error 156.0285101 478298.7014
2.05461264
4
Median 8475 28833410 77.2728259

POPULATION AND CRIME RATES 8
1
Mode #N/A #N/A #N/A
Standard
Deviation 810.7479207 2485312.956
10.6760804
7
Sample Variance 657312.1909 6.17678E+12
113.978694
1
Kurtosis -0.322824661 -1.280935054
-
0.90088210
3
Skewness 0.313961382 -0.068771016
0.44467671
5
Range 3096 7963463
35.8019096
6
Minimum 7246 24593000
64.1980903
4
Maximum 10342 32556463 100
Sum 230014 772698863
2155.77627
7
Count 27 27 27
The table above represents the measures of central tendency for population size, GDP,
and total crime in a year. The average annual crimes, population size, and GDP are 8519.04,
28618476.4, and 79.84 respectively. This suggests that the annual crime is approximately 8500

POPULATION AND CRIME RATES 9
with an approximated population of 28.6 million people living in Canada. Thus the expected
annual crimes in Canada at any given year are approximately 8500. This suggests that the
annual crime is approximately 8500 with an approximated population of 28.6 million people
living in Canada.
The median annual crimes, population size, and GDP are 8475, 28833410, and 77.27
respectively. This suggests that the median is approximately 8475 with an approximated
population of 28.8million people living in Canada. Thus middle most annual crimes in Canada at
any given is 8475.
2.4 Measures of Spread
The table above represents the measures of spread for population size, GDP, and total
crime in a year. The variance of total crimes, population size, and GDP are 657312.1909,
6.17678E+12, and 113.9786941 respectively. This suggests that the mean annual crime is
approximately 8500 with a variance of 657312.1909 and the mean population size is
approximately 28.6 million with a variance of 6.17678E+12. Similarly, the mean GDP of Canada
is 79.84 with a variance of 113.98.
The standard deviation of total crimes, population size, and GDP are 810.7479207,
2485312.956, and 10.67608047respectively. This suggests that the mean annual crime is
approximately 8500 with a standard deviation of 810.7479207 and the mean population size is
approximately 28.6 million with a standard deviation of 2485312.956. Similarly, the mean GDP
of Canada is 79.84 with a variance of 10.6760.Therefore, the predicted total crime, population
size, and GDP with the respective standard deviations.
2.5 Correlation Coefficient
correlation

POPULATION AND CRIME RATES 10
population
size GDP
Total
Crimes
population
size 1
GDP 0.947088776 1
Total Crimes -0.519068695
-
0.6810131
7 1
60.00 65.00 70.00 75.00 80.00 85.00 90.00 95.00 100.00105.00
0
2,000
4,000
6,000
8,000
10,000
12,000
f(x) = − 51.7165464339379 x + 12648.270516827
A scatterplot of total crimes against GDP
GDP
Crime rate
Under the correlation coefficient section, the relationship between variables is represented
graphically. The correlation coefficient between total crimes and GDP is 0.68. The fitted
regression model, y=-51.71x+12648.
A correlation coefficient 0.68 indicates a fairly strong positive correlation between the number of
crimes committee and income (GDP). An increase in income is likely to increase the crime rates

POPULATION AND CRIME RATES 11
in Canada. This supports the research hypothesis and proves that a fairly strong relationship exist
between the number of crime committed and the income. According to s
24000000 26000000 28000000 30000000 32000000 34000000
0
2,000
4,000
6,000
8,000
10,000
12,000
f(x) = − 0.000169328318995683 x + 13364.9555393209
Population size
C
r
i
m
e
s
The correlation coefficient between total crimes and GDP is 0.68. The fitted regression model,
y=-51.71x+12648.
A correlation coefficient 0.68 indicates a fairly strong positive correlation between the number of
crimes committee and income (GDP). An increase in income is likely to increase the crime rates
in Canada. This supports the research hypothesis and proves that a fairly strong relationship exist
between the number of crime committed and the income. According to

POPULATION AND CRIME RATES 12
Bar graph
representing the
number of police
officers in 100,000
per unit in 1986 and
2016
The above bar graph illustrates the number of police officers in 1986 and 2016. The results show
no significant change in number of police officers in 1986 and 2016 in any of the provinces.
These results indicate that the number of police officers does not have an effect on the decline of
crime in Canada. This information is useful in ruling out which factors affect crime and which do
not.
2.6 Linear Regression
2.6.1 Linear regression between crime rates and population size.
SUMMARY
OUTPUT
Regression
Statistics
Multiple R 0.519069
R Square 0.269432
Canada
N.L.
P.E.I.
N.S.
N.B.
Que.
Ont.
Man.
Sask.
Alta.
B.C.
0
50
100
150
200
250
Police Officers Per Province
1986
2016
Province
# of Poilice Officers

POPULATION AND CRIME RATES 13
Adjusted R
Square 0.24021
Standard Error 706.6962
Observations 27
ANOVA
df SS MS F
Significanc
e F
Regression 1 4604630 4604630
9.21996
4 0.005531
Residual 25 12485487
499419.
5
Total 26 17090117
Coefficient
s
Standard
Error t Stat P-value Lower 95%
Upper
95%
Intercept 13364.96 1601.706 8.3442
1.08E-
08 10066.18
16663.7
3
Population size -0.00017 5.58E-05
-
3.03644
0.00553
1 -0.00028 -5.4E-05

POPULATION AND CRIME RATES 14
A linear regression model developed to determine the relationship between population size and
crime rate showed a moderate relationship between the two variables. The fitted regression
model was found to be:
Crime Rate = 13364.96-0.00017 * population size
Interpretation
A one unit increase in population size leads to a 0.00017 decrease in crime rate and vice
versa. The correlation of determination and correlation coefficient value are 0.52 and 0.27
respectively. Therefore, the fitted regression model explains 52% of the dependent value (crime
rate). At α=0.05, the observed p value is 0.0055 which is less than 0.05 thus the fitted regression
model is statistically significant in explaining the dependent variable (crime rate).
2.6.2 Linear regression between crime rates and Gross Domestic product (GDP)
SUMMARY
OUTPUT
Regression
Statistics
Multiple R 0.681013
R Square 0.463779
Adjusted R
Square 0.44233
Standard Error 605.4447
Observations 27

POPULATION AND CRIME RATES 15
ANOVA
df SS MS F
Significanc
e F
Regression 1 7926036.28 7926036
21.6225
6 9.23E-05
Residual 25 9164080.683
366563.
2
Total 26 17090116.96
Coefficient
s Standard Error t Stat P-value Lower 95%
Upper
95%
Intercept 12648.27 895.6176221 14.1224
2.03E-
13 10803.71
14492.8
3
GDP -51.7165 11.12182188
-
4.65001
9.23E-
05 -74.6224
-
28.8107
A linear regression model developed to determine the relationship between GDP and crime rate
showed a moderate relationship between the two variables. The fitted regression model was
found to be:
Crime Rate = 13364.96-51.7165 * GDP
Interpretation
A one unit increase in GDP leads to a -51.72 decrease in crime rate and vice versa. The
correlation coefficient and correlation of determination value are 0.68 and 0.46 respectively.

POPULATION AND CRIME RATES 16
Therefore, the fitted regression model explains 68% of the dependent value (crime rate). At α
=0.05, the observed p value is 9.23E-05 which is less than 0.05 thus the GDP is statistically
significant in explaining the dependent variable (crime rate).
3.0 conclusion
Throughout this report the topic of crime rates has been analyzed and what has
contributed to its decline through the past few decades. It is seen that a few factors influence this,
such as the effect of the baby boom in various ages and the shift in population demographics.
The hypothesis was proven correctly verifying that population size does affect the number of
crimes .Crime rates rose from 1967 to 1985 when the baby boomers were at the age of 21 and
then decreased after they all turned 25. This is a major factor in examining crime thus proving
that population demographics does affect crime rates. It is important to note there are few other
predictions as to why crime may have decreased such as an increase in police officers, but this
was proven false in figure 11 which analyzed that the number of police officers from 1986 to
2016 has not increased and this can be ruled out as affecting the decrease. A bias which could
have arisen throughout this report would which data was chosen to be included and which data
was left out. This other data that was not have chosen could have proved the hypothesis wrong If
included or strained it. By choosing this other data the hypothesis was proved correct.
Year
population
size GDP
Total
Crimes
1980 24593000 65.81 8,343
1981 24900000 67.02 8,736
1982 25202000 64.20 8,773

POPULATION AND CRIME RATES 17
1983 25456000 65.41 8,470
1984 25702000 68.50 8,387
1985 25942000 71.53 8,413
1986 26204000 72.67 8,727
1987 26550000 74.65 8,957
1988 26895000 77.27 8,919
1989 27379000 77.74 8,892
1990 27791000 76.78 9,485
1991 28171680 74.27 10,342
1992 28519600 73.85 10,040
1993 28833410 74.55 9,538
1994 29111910 77.22 9,125
1995 29354000 78.41 9,008
1996 29671900 78.71 8,932
1997 29987200 81.18 8,475
1998 30247900 83.60 8,093
1999 30499200 87.35 7,695
2000 30769700 91.00 7,610
2001 31081900 91.68 7,592
2002 31362000 93.58 7,516
2003 31630000 94.53 7,773
2004 31989000 96.21 7,601
2005 32299000 98.05 7,326

POPULATION AND CRIME RATES 18
2006 32556463 100.00 7,246
Year
Amount of Births in
thousands
1940 2,559
1941 2,703
1942 2,989
1943 3,104
1944 2,939
1945 2,858
1946 3,411
1947 3,817
1948 3,637
1949 3,649
1950 3,632
1951 3,823
1952 3,913
1953 3,965
1954 4,078
1955 4,097
1956 4,218
1957 4,300
1958 4,255

POPULATION AND CRIME RATES 19
1959 4,245
1960 4,258
1961 4,268
1962 4,167
1963 4,098
1964 4,027
1965 3,760
1966 3,606
1967 3,521
1968 3,502
1969 3,606
1970 3,731
1971 3,556
1972 3,258
1973 3,137
1974 3,160
1975 3,144
1976 3,168
1977 3,327
1978 3,333
1979 3,494
1980 3,612
1981 3,629

POPULATION AND CRIME RATES 20
1982 3,681
1983 3,639
1984 3,669
1985 3,761
1986 3,757
1987 3,809
1988 3,910
1989 4,041
1990 4,158
1991 4,111
1992 4,065
1993 4,000
1994 3,979
Year Violent crimes Property crimes Other crimes Total crimes
1962 221 1,891 659 2,771
1963 249 2,047 726 3,022
1964 284 2,146 815 3,245
1965 299 2,091 809 3,199
1966 347 2,258 907 3,511
1967 381 2,484 985 3,850
1968 423 2,826 1,087 4,336
1969 453 3,120 1,164 4,737

POPULATION AND CRIME RATES 21
1970 481 3,515 1,217 5,212
1971 492 3,649 1,170 5,311
1972 497 3,634 1,224 5,355
1973 524 3,704 1,546 5,773
1974 553 4,151 1,684 6,388
1975 585 4,498 1,769 6,852
1976 584 4,533 1,867 6,984
1977 572 4,466 1,933 6,971
1978 580 4,579 1,995 7,154
1979 610 4,903 2,153 7,666
1980 636 5,444 2,263 8,343
1981 654 5,759 2,322 8,736
1982 671 5,840 2,262 8,773
1983 679 5,608 2,182 8,470
1984 701 5,501 2,185 8,387
1985 735 5,451 2,227 8,413
1986 785 5,550 2,392 8,727
1987 829 5,553 2,575 8,957
1988 868 5,439 2,613 8,919
1989 911 5,289 2,692 8,892
1990 973 5,612 2,900 9,485
1991 1,059 6,160 3,122 10,342
1992 1,084 5,904 3,052 10,040

POPULATION AND CRIME RATES 22
1993 1,082 5,575 2,881 9,538
1994 1,047 5,257 2,821 9,125
1995 1,009 5,292 2,707 9,008
1996 1,002 5,274 2,656 8,932
1997 993 4,880 2,603 8,475
1998 995 4,569 2,529 8,093
1999 971 4,276 2,449 7,695
2000 996 4,081 2,534 7,610
2001 995 4,004 2,593 7,592
2002 980 3,976 2,560 7,516
2003 978 4,125 2,670 7,773
2004 957 3,976 2,668 7,601
2005 962 3,744 2,620 7,326
2006 968 3,605 2,673 7,246
2007 952 3,335 2,621 6,908
2008 938 3,096 2,598 6,632
2009 926 3,005 2,531 6,462
2010 907 2,802 2,451 6,160
2011 869 2,586 2,324 5,780
2012 841 2,521 2,269 5,632
2013 766 2,342 2,082 5,191
References

POPULATION AND CRIME RATES 23
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POPULATION AND CRIME RATES 24