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Current Population Survey Paper

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Introduction (State and Plan) As a group of young adults, we are interested in the correlation of a person’s age and their total family income. We chose these variables because we want to learn if the general assumption of total family income increases as a person ages is true. Especially since most people tend to get promotions in their respective career fields over time leading to an increase in wages or get married leading to a general increase in total family income. In order to study these variables, a statistical analysis of age and total family income is needed. For this we will compare the two quantitative discrete variables, total family income and age, from the Current Population Survey (CPS) data set using histograms, a …show more content…

This means the data was statistically significant and we can reject the null hypothesis. The alternative hypothesis states that as an individual ages after the age of 18, their total family income will increase. A two way table test for homogeneity for a characteristic distribution was performed to analyze the data which included two populations, 18-45 and 45-96 age groups. Individuals between the ages of 45-96 have a higher total family income in the income brackets of $0-$60,000 and $60,000-$250,000. However, a Type I Error may have occurred where the null hypothesis was rejected, but in fact was true. This means that individuals between the ages of 18-45 do have a total family income greater than or equal to the individuals between the ages of 45-96. A consequence of this this error could be that individuals between the ages of 18-45 going to jail for tax fraud. A Type II Error on the other hand, would mean that we failed to reject the null hypothesis when the null hypothesis is in fact false. This means that individual's total family income between the ages of 18-45 is not greater than or equal to the total family income of individuals between the ages of 45-96. A consequence of this could be the government believing that individuals in the 18-45 age range make more money than what they actually do thus failing to allot the necessary financial and government

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