R Dataset / Package Stat2Data / CAFE

On this R-data statistics page, you will find information about the CAFE data set which pertains to CAFE. The CAFE data set is found in the Stat2Data R package. You can load the CAFE data set in R by issuing the following command at the console data("CAFE"). This will load the data into a variable called CAFE. If R says the CAFE data set is not found, you can try installing the package by issuing this command install.packages("Stat2Data") and then attempt to reload the data with the library() command. If you need to download R, you can go to the R project website. You can download a CSV (comma separated values) version of the CAFE R data set. The size of this file is about 4,712 bytes.

CAFE

Description

Senate votes for Corporate Average Fuel Economy (CAFE) bill

Format

A dataset with 100 observations on the following 7 variables.

R project statistics dataset table
Senator Senator's name
State Code for senator's state
Party party affiliation: D=Democrat, I=Independent, R=Republican
Contribution Contributions from car manufactures (dollars)
LogContr Log of (Contribution+1)
Dem 1=Democrat/Indpendent 0=Republican
Vote 1=yes or 0=no

Details

The Corporate Average Fuel Economy (CAFE) bill was proposed by Senators John McCain and John Kerry to improve the fuel economy of cars and light trucks sold in the United States. However a critical vote on an amendment in March of 2002 threatened to indefinitely postpone CAFE. The amendment charged the National Highway Traffic Safety Administration to develop a new standard, the effect being to put on indefinite hold the McCain-Kerry bill. It passed by a vote of 62-38. A political question of interest is whether there is evidence of monetary influence on a senator's vote. Scott Preston, a professor of statistics at SUNY, Oswego, collected data on this vote which includes the vote of each senator (1=Yes or 0=No) and monetary contributions that each of the 100 senators received over his or her lifetime from the car manufacturers.

Source

Thanks to Prof. Scott Preston for the data.

Dataset imported from https://www.r-project.org.

Attachments: csv, json

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