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

## # A tibble: 173 x 22
##        X  Rank Major_code Major Total   Men Women Major_category ShareWomen
##    <int> <int>      <int> <fct> <int> <int> <int> <fct>               <dbl>
##  1     1     1       2419 PETR~  2339  2057   282 Engineering         0.121
##  2     2     2       2416 MINI~   756   679    77 Engineering         0.102
##  3     3     3       2415 META~   856   725   131 Engineering         0.153
##  4     4     4       2417 NAVA~  1258  1123   135 Engineering         0.107
##  5     5     5       2405 CHEM~ 32260 21239 11021 Engineering         0.342
##  6     6     6       2418 NUCL~  2573  2200   373 Engineering         0.145
##  7     7     7       6202 ACTU~  3777  2110  1667 Business            0.441
##  8     8     8       5001 ASTR~  1792   832   960 Physical Scie~      0.536
##  9     9     9       2414 MECH~ 91227 80320 10907 Engineering         0.120
## 10    10    10       2408 ELEC~ 81527 65511 16016 Engineering         0.196
## # ... with 163 more rows, and 13 more variables: Sample_size <int>,
## #   Employed <int>, Full_time <int>, Part_time <int>,
## #   Full_time_year_round <int>, Unemployed <int>, Unemployment_rate <dbl>,
## #   Median <int>, P25th <int>, P75th <int>, College_jobs <int>,
## #   Non_college_jobs <int>, Low_wage_jobs <int>

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

The sixth observation is nuclear engineering with a total of 2573 graduates, it’s in the engineering major category, the share of women is about 14.5 percent and the sample size is 17, the unemployment rate is 17.7 percent and median income is 65000.

Q2. Which major has the highest share of men?

Military Technologies.

Q3. Which major has the highest median earnings?

Petroleum Engineering.

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

Military Technologies because it has no share of women.

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

Hint: Use the same code as above for the scatterplot, but convert the numbers on both axes to the percent format.

Q6. Decribe the relationship between ShareWomen and Unemployment_rate.

Hint: There are many resources available regarding how to interpret scatter plots. For example, Google something like, “interpreting scatter plots positive or negative”. Discuss whether the regression line is upward sloping, downward sloping, or more or less flat. What does this mean regarding the relationship between the two variables?

The scatterplot showing a very slight upward slope means that the more share women have in a major, the higher the unemployment rate will be, although very slightly because of how slight the slope is.

Q7. Which Major_category appears to have the lowest Unemployment_rate AND the smallest share of women?

Hint: Don’t consider Other but only the top four Major_category.

Engineering has the lowest unemployment rate and smallest share of women.

Q8. Hide the code but display the results of the code on the webpage.

Q9. Display the title and your name correctly at the top of the webpage.

Q10. Use the correct slug.