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Data Management Data Management Culminating ProjectCulminating Project
Factors That Affect Income of Canadians
By: Jodi Morden & Mike CurridorSacred Heart High School, Ottawa
Factors InvestigatedFactors Investigated
Location, Sex, Age, and Education
HypothesisHypothesis
All of these factors contribute to the fluctuation of one’s income
Therefore living in a big city, being male, between 25-35 years of age, and having a university level education. Causes one to have a higher income.
Location: CityLocation: City
Average Income of the 5 largest cities in Canada: $54,469(Toronto, Montreal, Vancouver, Ottawa, Calgary)
Average Income of the 20 Other Largest Cities in Canada: $47,952
0
20000
40000
60000
Average Income
The Big 5 Other 20
Average Income of Cities
City Average Income
Toronto $60,110
Montreal $44,593
Vancouver $54,055
Ottawa $56,760
Calgary $56,829
0
20000
40000
60000
80000
Income
The Big 5
Toronto Montreal Vancouver Ottaw a Calgary
We can conclude that living in a big city affects one’s income. However, your income may also affect one living in a big city. Therefore we can conclude that there is a relationship, but that it is causal. Also the city has a direct correlation with the type of work. Due to a uniform graph, we can see no major difference between the cities.
Measures of SpreadMeasures of Spread
•Mean: $54,469
•Median: Ottawa ($56,670)
•Standard Deviation: 5298.3
Location: ProvinceLocation: ProvinceProvince Average Income
Newfoundland $41,064
PEI $42,028
Nova Scotia $41,446
New Brunswick $41,090
Quebec $42,229
Ontario $54,291
Manitoba $43,404
Saskatchewan $42,685
Alberta $51,118
British Columbia $50,667
Yukon $54,953
Northwest Territories $60,506
Average Provincial Income
4268543404
54291
4222941090
4144642028
41064
5111850667
5495360506
NFLDPEINSNB
QueOnt
ManSaskAltbBC
YukNWT
Pro
vin
ce
We can see that the Yukon and the Northwest Territories have the highest income. Although this may appear odd at first, if investigated it makes quite a bit of sense. There is essentially no unemployed people in these provinces, because most of the unemployed moved south to find work. The employed people who do live there are given special incentives by their employer to live there ( i.e. more money). Therefore the small number of people that do live there are making a large sum of money.
Measures of SpreadMeasures of Spread
•Median: $43,044.50
•Mean: $47,123.42
•Standard Deviation: 6513.37
SexSex
0 50 100 150 200 250
Frequency
$0-$19,999
$20,000-$39,999
$40,000-$59,999
$60,000-$79,999
$80,000-$99,999
$100,000+
Income VS. Sex
Males Females
Income Males Females
$0-$19,999 93 141
$20,000-$39,999 107 100
$40,000-$59,999 73 28
$60,000-$79,999 25 7
$80,000-$99,999 6 1
$100,000+ 3 2
The number of males and females earning a high income ($100,000+) are relatively low, but equal. As we move down the income brackets the division becomes more and more. Eventually leveling back off at the lower income brackets. We can interrupt this in saying, woman either have a very small or very large income. Therefore the majority of the middle earners are male.
Measures of SpreadMeasures of Spread Skewed Right
Mean: Males: $33,810.58Females: $23,619.58
Median: Males: $0-$19,999Females: $20,000-$39,999
Mode: Males: $20,000-$39,999Females: $0-$19,999
StandardDeviation: Males: 21 220.21
Females: 17 022.43
Age Age Source: 1991 Census microdataSource: 1991 Census microdata
Income Vs. Age
0
20000
40000
60000
80000
100000
120000
140000
0 20 40 60 80 100
Age
Inco
me
The income of people increases from 18, and peaks around 50. Then takes a sharp decline. Except for certain outliers, we can conclude that once a person passes the age of 50 their income declines. This is mainly because of inability to work full days and the retirement factor. All these can contribute to the decline in wages and number of hours worked daily. This graph shows a strong positive correlation, which further substantiates the affect that age has on one’s income.
EducationEducationIncome of $0-$39,999
16%
25%
40%
19%Highschool
Less than Highschool
Less than University
University
Income of $40,000-$79,999
13%
33%36%
18%
Highschool
Less than Highschool
Less than University
University
Measures of SpreadMeasures of Spread
•Mode: $0-$39,999- Less than University 40%$40,000-$79,999- Less than University 36%$80,000+- Less than High school 59%
*Mode is only applicable to this data set.
The data was surprising with respect to the high income earners. This was because 56% of the high income earners had education of less than high school. Even within the middle income bracket, the majority of earners had an education of less than university. Therefore we can see no evidence which supports our original prediction.
Summarization Summarization To recap- we predicted that the most important factors that affect a
person’s income are location, sex, age, and education. We predicted that living in a big city, being male, being between the age of 35 and 45, and having a university level education.
The first factor that we looked at was location, we concluded that if you live in a big city, to be more precise Toronto, you are more likely to earn a higher income. Also we determined that this relationship was causal.
The second factor that we looked at was sex, we discovered that males earn more on average than females.
The third factor that we looked at was age, we found that at the age of 18 a person’s income increased steadily. Peaked around 50 years old, and began to decrease afterwards.
The final factor that we looked at was education. From the examination we discovered a surprising twist in the data, it showed that the majority of high income earners had an education less than high school.
ConclusionsConclusions
From the data that we have analyzed, we can predict that being male, living in a big city, being 35-45 years of age, increase one’s chance of high income.
We were incorrect with our initial prediction of education. A possibility to explain the number of high income earners who had a less than high school education could be, taking over a family run company. The person knows they have a well paying job once they leave school, therefore they may see school as unnecessary.
SourcesSources
Statistics Canada 2001 Census – Average Income based on location (province, CMA)
Statistics Canada Micro data from the 1991 Census – Income based on Sex, Education, and Age