Grounding our assumptions in Human Capital theory, we endeavoured to investigate the relationship between an individualās educational attainment and their income. Due to contradicting explanations in the literature, we factored in several other control variables including age, race, gender, hours worked, and province of residence. We included these variables in an attempt to isolate the relationship between education and income. Our null hypothesis was that there is no significant association between education level and annual personal income, and our alternative hypothesis was that there was some significant association between education level and income.
In an exploratory analysis, we identified that the highest correlation level among all variables within the data set was 0.4, between education level and income. With this finding, we felt confident that there would be a relationship between the two variables, and decided to perform a multiple linear regression analysis.
After conducting the multiple linear regression, we found that approximately 50% of the variance in personal annual income could be explained by level of education when controlling for age, sex, race, and hours worked per week. With p < .001, we identified that education, sex, and race all had some significant effect on income level. There were some variations in income across provinces, with an individual making less in Quebec and more in Alberta, when compared to Ontario. Additionally, someone who worked less than 40 hours per week is expected to make less than someone who does. After the 40 hour mark, though, the number of hours worked does not significantly affect the level of income.
With all of our findings and results, we believe there is enough evidence to reject the null hypothesis - there is a significant relationship between education and income. Ā
