schooling earnings 0 12.5572 1 12.37059 2 12.28345 3 12.53942 4 13.60204 5 13.69685 6 14.46392 7 15.48792 8 16.58223 9 17.75331 10 18.31583 11 18.93581 12 20.69255 13 22.40492 14 23.55711 15 25.12731 16 30.9133 17 30.25502 18 31.35148 19 31.24208 20 34.62525

The file "SchoolEarnings.csv" contains data on earnings and schooling. The data is from a 1991 study by Angrist and Krueger entitled "Does Compulsory School Attendance Affect Schooling and Earnings?"published in the Quarterly Journal of Economics. Angrist and Krueger obtained their data from the Integrated Public Use Microdata Series from the 1980 U.S. Census. The study specifically focused on men born between 1930 and 1939, so they were 41-50 years old at the time of data collection. Each row corresponds to a large group of men with the same level of schooling. The variable "schooling" indicates the years of schooling for each group. 12 corresponds with high school completion, and 16 corresponds with college completion. The variable "earnings" indicates the average annual earnings (in 1980 U.S. dollars) for the men in each group.

Question: Let's dig more deeply into whether the relationship between earnings and schooling is approximately linear.

Start by making a scatterplot, using the Excel guidance page's instructions for "How to make a linear regression graph in excel".

Add to the scatterplot the line of best fit (Excel calls this a linear trendline, and this is the same line produced in your regression estimate). Include the resulting plot in your answer as an image file.

Does this regression line look like it fits the data well?