Step into the role of a government official or an economist who wants to increase the prosperity of people in their country. This is a very difficult task. How would you do this? Coming up with a good government policy requires an understanding of how currently things work. How are people's earnings determined? Only then can we formulate sensible policies. Today you will use what you learned about multivariable regression to build a model for predicting people's earnings. You will then analyse your model and try to improve it.

But first, we have to get to grips with the data.

Understand the National Longitudinal Survey of Youth 1997–

This dataset is one of the most important databases available to social scientists working with US data. It allows scientists to look at the determinants of earnings as well as educational attainment and has incredible relevance for government social policy. In particular, it can shed light on politically sensitive issues like how different educational attainment and salaries are for people of different ethnicity, sex, and other factors.

The National Longitudinal Survey of Youth 1997– is a panel survey with repeated interviews of a nationally representative sample of young men and women aged 12 to 18 in 1997 in the United States (note - all the expenditure is measured in US dollars). Until 2011 the interviews for the NLSY97– took place annually and are now being conducted at two-year intervals. The core sample originally consisted of 3,459 males and 3,289 females. For this assignment, I have included only a subset of the data.

If you were to look online you would find that there exist also special supplementary samples of ethnic minorities. Extensive background information was obtained in the base-year survey in 1997 and since then information has been updated each year on education, training, employment, marital status, fertility, health, child care and assets and income. The surveys have been very detailed and implemented with the highest quality. Very impressive work!