For information about the data, click the link here. https://github.com/rfordatascience/tidytuesday/tree/master/data/2018/2018-10-16

Q1. Describe the sixth observation, using Major, Total, Major_category, ShareWomen, Sample_size, Unemployment_rate, and Median.

The sixth observation, Nuclear Engineering, is in the Engineering category and has a total of 2573 recent graduates. 373 of those graduates are women, resulting in a 14.49% share. The sample size is 17 individuals for this study. Unemployment rate is high for this major at 17.72%, but the median income is also high at $65000.

Q2. Which major has the highest share of men?

The major with the highest share of men is Military Technologies, having a 100% share of male graduates.

Q3. Which major has the highest median earnings?

The major with the highest median earnings is Petroleum Engineering, with median earnings at $110,000.

Q4. Which major does the regression model predict to have the highest median earnings?

The regression model predicts Petroleum Engineering to have the highest median earnings.

Q5. Create the same scatterplot to examine the relationship between ShareWomen and Unemployment_rate.

Q6. Decribe the relationship between ShareWomen and Unemployment_rate.

There is a very weak positive correlation between unemployment rate and the share of women in a major. The regression slope is almost flat, indicating there is not much of a correlation between the two.

Q7. Which Major_category appears to have the lowest Unemployment_rate?

The Education major category appears to have the lowest unemployment rate, as most of the majors in it fall below the r-slope.