Data Management Culminating Project

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Data Management Culminating Project
Factors That Affect Income of Canadians
By Jodi Morden Mike Curridor
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Factors Investigated

• Location, Sex, Age, and Education

Hypothesis

• All of these factors contribute to the
  fluctuation of ones 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.

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Location!!!
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Location 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
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We can conclude that living in a big city affects
ones 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.
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Measures of Spread

• Mean 54,469
• Median Ottawa (56,670)
• Standard Deviation 5298.3

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Location Province
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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.
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Measures of Spread

• Median 43,044.50
• Mean 47,123.42
• Standard Deviation 6513.37

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Sex!!!
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Sex
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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.
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Measures of Spread

• Skewed Right
• Mean Males 33,810.58
• Females 23,619.58
• Median Males 0-19,999
• Females 20,000-39,999
• Mode Males 20,000-39,999
• Females 0-19,999
• Standard
• Deviation Males 21 220.21
• Females 17 022.43

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Age!!!
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Age
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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 ones
income.
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Education!!!
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Education
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Measures 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.
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Summarization

• To recap- we predicted that the most important
  factors that affect a persons 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 persons 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.

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Conclusions

• 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 ones 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.

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Sources

• 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

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The End
Thank You