Quantifying Evidence for Outlierness

Description

The data are Democratic and Republican vote counts, by (a) absentee ballot and (b) voting machine, for 22 elections in Philadelphia's senatorial districts between 1982 and 1993.

Usage

1

Format

A data frame with 22 observations on the following 2 variables.

Year

Year of election

District

a factor with levels "D1", "D2", "D3", "D4", "D5", "D7", and "D8"

DemAbsenteeVotes

Number of absentee ballots indicating a vote for the Democratic candidate

RepubAbsenteeVotes

Number of absentee ballots indicating a vote for the Republican candidate

DemMachineVotes

Number of machine-counted ballots indicating a vote for the Democratic candidate

RepubMachineVotes

Number of machine-coutned ballots indicating a vote for the Republican candidate

DemPctOfAbsenteeVotes

Percentage of absentee ballots indicating a vote for the Democratic candidate

DemPctOfMachineVotes

Percentage of machine-counted ballots indicating a vote for the Democratic candidate

Disputed

a factor taking on the value "yes" for the disputed election and "no" for all other elections

Details

In a special election to fill a Pennsylvania State Senate seat in 1993, the Democrat, William Stinson, received 19,127 machine–counted votes and the Republican, Bruce Marks, received 19,691. In addition, there were 1,391 absentee ballots for Stinson and 366 absentee ballots for Marks, so that the total tally showed Stinson the winner by 461 votes. The large disparity between the machine–counted and absentee votes, and the resulting reversal of the outcome due to the absentee ballots caused some concern about possible illegal influence on the absentee votes. To see whether the discrepancy in absentee votes was larger than could be explained by chance, an econometrician considered the data given in this data frame (read from a graph in The New York Times, 11 April 1994).

Source

Ramsey, F.L. and Schafer, D.W. (2013). The Statistical Sleuth: A Course in Methods of Data Analysis (3rd ed), Cengage Learning.

References

Ashenfelter, O (1994). Report on Expected Absentee Ballots. Department of Economics, Princeton University. See also Simon Jackman (2011). pscl: Classes and Methods for R Developed in the Political Science Computational Laboratory, Stanford University. Department of Political Science, Stanford University. Stanford, California. R package version 1.03.10. http://pscl.stanford.edu/

Examples

1

Want to suggest features or report bugs for rdrr.io? Use the GitHub issue tracker.