Exercise

# Modeling eBay auctions

Sometimes modeling a whole dataset suggests trends that disagree with models on separate parts of that dataset. This is known as Simpson's paradox. In the most extreme case, you may see a positive slope on the whole dataset, and negative slopes on every subset of that dataset (or the other way around).

Over the next few exercises, you'll look at eBay auctions of Palm Pilot M515 PDA models.

variable | meaning |
---|---|

`price` |
Final sale price, USD |

`openbid` |
The opening bid, USD |

`auction_type` |
How long did the auction last? |

`auctions`

is available; `dplyr`

and `ggplot2`

are loaded.

Instructions 1/2

**undefined XP**

- Look at the structure of the
`auctions`

dataset and familiarize yourself with its columns. - Fit a linear regression model of
`price`

versus`openbid`

, using the`auctions`

dataset.*Look at the coefficients.*