Eco Data

This essay shall use data from “collection set D” to analyse and decide whether being married affects the earnings of male subjects. We will use the data of whether a man is single, divorced or married and compare it with earnings. We shall also include hours that are worked each week, how much work experience (out of school) the male has and his tenure (how many years he has worked for his employer).

Earning is our dependant variable whereas hours worked per week, work experience and tenure are our independent variables as well as marital status.

This question is of interest as many people ponder the fact of why male’s marital status could affect earnings. It is of general knowledge that a married man usually earns more than one with no relationship but rarely do people find why this is or if it is true. Being married doesn’t appear to have any immediate links with a person’s job but surely this cannot be true if earnings are affected. It is my intention to discover the truth behind this.

What we know; generally a man who works more; a man who works harder earns more money. This is completely determined by the particular job the particular man has. For example working 50 hours a week in a supermarket will more than likely (even with 20 more hours) earn less than a man who works 30 hours a week as a dentist. Tenure; working longer for an employer usually opens more promotion opportunities which may lead to a pay rise. Experience is always important to an employer and may result in person getting a higher paid job. However it does not guarantee a job so may not play a role in earnings. Some jobs will look for people with more experience and may even pay more for people who have experience for the same job.

R(squared) in a regression tells us the correlation between the dependant and independent variables. R(squared) is 0.0439 in our first regression. This tells us there is a 4.39% correlation between our dependant variable and the three independent...