R Dataset / Package HSAUR / voting

How To Create a Barplot

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How To Create a Stacked Barplot

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How To Create a Pie Chart

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How To Compute the Mean

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How To Create a Plot

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How to Compute the Median

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Boxplot

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Correlation Coefficient

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Cumulative Frequency Histogram

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Dotplot

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Hollow Histogram

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Numerical Summaries

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Pie Chart

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Plot

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Ratio

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Regression

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Stem and Leaf Plots

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Visual Summaries

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Submitted by pmagunia on March 9, 2018 - 1:06 PM
<iframe src="https://embed.picostat.com/r-dataset-package-hsaur-voting.html" frameBorder="0" width="100%" height="307px" />
Attachment Size
dataset-15421.csv 402 bytes
Dataset License
GNU General Public License v2.0
Documentation License
GNU General Public License v2.0
Documentation

On this Picostat.com statistics page, you will find information about the voting data set which pertains to House of Representatives Voting Data . The voting data set is found in the HSAUR R package. Try to load the voting data set in R by issuing the following command at the console data("voting"). This may load the data into a variable called voting. If R says the voting data set is not found, you can try installing the package by issuing this command install.packages("HSAUR") and then attempt to reload the data with library("HSAUR") followed by data("voting"). Perhaps strangley, if R gives you no output after entering a command, it means the command succeeded. If it succeeded you can see the data by typing voting at the command-line which should display the entire dataset.

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 voting R data set. The size of this file is about 402 bytes.


House of Representatives Voting Data

Description

Voting results for 15 congressmen from New Jersey.

Usage

data("voting")

Format

A 15 times 15 matrix.

Details

Romesburg (1984) gives a set of data that shows the number of times 15 congressmen from New Jersey voted differently in the House of Representatives on 19 environmental bills. Abstentions are not recorded.

Source

H. C. Romesburg (1984), Cluster Analysis for Researchers. Lifetime Learning Publications, Belmont, Canada.

Examples

  data("voting", package = "HSAUR")
  require("MASS")
  voting_mds <- isoMDS(voting)
  plot(voting_mds$points[,1], voting_mds$points[,2],
       type = "n", xlab = "Coordinate 1", ylab = "Coordinate 2",
       xlim = range(voting_mds$points[,1])*1.2)
  text(voting_mds$points[,1], voting_mds$points[,2], 
       labels = colnames(voting))
  voting_sh <- Shepard(voting[lower.tri(voting)], voting_mds$points)
--

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