15.6 Test your might! A ship auction
The following questions apply to the auction dataset in the yarrr package. This dataset contains information about 1,000 ships sold at a pirate auction. Here’s how the first few rows of the dataframe should look:
head(auction)
## cannons rooms age condition color style jbb price
## 1 18 20 140 5 red classic 3976 3502
## 2 21 21 93 5 red modern 3463 2955
## 3 20 18 48 2 plum classic 3175 3281
## 4 24 20 81 5 salmon classic 4463 4400
## 5 20 21 93 2 red modern 2858 2177
## 6 21 19 60 6 red classic 4420 3792The column jbb is the “Jack’s Blue Book” value of a ship. Create a regression object called
jbb.cannon.lmpredicting the JBB value of ships based on the number of cannons it has. Based on your result, how much value does each additional cannon bring to a ship?Repeat your previous regression, but do two separate regressions: one on modern ships and one on classic ships. Is there relationship between cannons and JBB the same for both types of ships?
Is there a significant interaction between a ship’s style and its age on its JBB value? If so, how do you interpret the interaction?
Create a regression object called
jbb.all.lmpredicting the JBB value of ships based on cannons, rooms, age, condition, color, and style. Which aspects of a ship significantly affect its JBB value?Create a regression object called
price.all.lmpredicting the actual selling value of ships based on cannons, rooms, age, condition, color, and style. Based on the results, does the JBB do a good job of capturing the effect of each variable on a ship’s selling price?Repeat your previous regression analysis, but instead of using the price as the dependent variable, use the binary variable price.gt.3500 indicating whether or not the ship had a selling price greater than 3500. Call the new regression object
price.all.blr. Make sure to use the appropriate regression function!!Using
price.all.lm, predict the selling price of the 3 new ships below
| cannons | rooms | age | condition | color | style |
|---|---|---|---|---|---|
| 12 | 34 | 43 | 7 | black | classic |
| 8 | 26 | 54 | 3 | black | modern |
| 32 | 65 | 100 | 5 | red | modern |
- Using
price.all.blr, predict the probability that the three new ships will have a selling price greater than 3500.