# ex0820: Quantifying Evidence for Outlierness In Sleuth3: Data Sets from Ramsey and Schafer's "Statistical Sleuth (3rd Ed)"

## 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` ```ex0820 ```

## 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"`

Number of absentee ballots indicating a vote for the Democratic candidate

Number of absentee ballots indicating a vote for the Republican candidate

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

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

Percentage of absentee ballots indicating a vote for the Democratic candidate

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` ```str(ex0820) ```

### Example output

```'data.frame':	22 obs. of  9 variables:
\$ Year                 : int  82 82 82 84 84 84 84 86 86 86 ...
\$ District             : Factor w/ 7 levels "D1","D2","D3",..: 2 4 7 1 3 5 6 2 4 7 ...
\$ DemAbsenteeVotes     : int  551 594 338 1357 716 1207 929 609 666 477 ...
\$ RepubAbsenteeVotes   : int  205 312 115 764 144 1436 258 316 306 171 ...
\$ DemMachineVotes      : int  47767 44437 55662 58327 78270 54812 77136 39034 52817 48315 ...
\$ RepubMachineVotes    : int  21340 28533 13214 38883 6473 55829 13730 23363 16541 11605 ...
\$ DemPctOfAbsenteeVotes: num  72.9 65.6 74.6 64 83.3 45.7 78.3 65.8 68.5 73.6 ...
\$ DemPctOfMachineVotes : num  69.1 60.9 80.8 60 92.4 49.5 84.9 62.6 76.2 80.6 ...
\$ Disputed             : Factor w/ 2 levels "no","yes": 1 1 1 1 1 1 1 1 1 1 ...
```

Sleuth3 documentation built on May 29, 2017, 11:28 a.m.