R Dataset / Package wooldridge / alcohol

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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Regression

Stem and Leaf Plots

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Visual Summaries

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Embed
<iframe src="https://embed.picostat.com/r-dataset-package-wooldridge-alcohol.html" frameBorder="0" width="100%" height="307px" />
Attachment Size
dataset-82096.csv 1.41 MB
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 alcohol data set which pertains to alcohol. The alcohol data set is found in the wooldridge R package. You can load the alcohol data set in R by issuing the following command at the console data("alcohol"). This will load the data into a variable called alcohol. If R says the alcohol data set is not found, you can try installing the package by issuing this command install.packages("wooldridge") and then attempt to reload the data. 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 alcohol R data set. The size of this file is about 1,482,997 bytes.


alcohol

Description

Data loads lazily. Type data(alcohol) into the console.

Usage

data(alcohol)

Format

A data.frame with 9822 rows and 33 variables:

  • abuse. =1 if abuse alcohol

  • status. out of workforce = 1; unemployed = 2, employed = 3

  • unemrate. state unemployment rate

  • age. age in years

  • educ. years of schooling

  • married. =1 if married

  • famsize. family size

  • white. =1 if white

  • exhealth. =1 if in excellent health

  • vghealth. =1 if in very good health

  • goodhealth. =1 if in good health

  • fairhealth. =1 if in fair health

  • northeast. =1 if live in northeast

  • midwest. =1 if live in midwest

  • south. =1 if live in south

  • centcity. =1 if live in central city of MSA

  • outercity. =1 if in outer city of MSA

  • qrt1. =1 if interviewed in first quarter

  • qrt2. =1 if interviewed in second quarter

  • qrt3. =1 if interviewed in third quarter

  • beertax. state excise tax, $ per gallon

  • cigtax. state cigarette tax, cents per pack

  • ethanol. state per-capita ethanol consumption

  • mothalc. =1 if mother an alcoholic

  • fathalc. =1 if father an alcoholic

  • livealc. =1 if lived with alcoholic

  • inwf. =1 if status > 1

  • employ. =1 if employed

  • agesq. age^2

  • beertaxsq. beertax^2

  • cigtaxsq. cigtax^2

  • ethanolsq. ethanol^2

  • educsq. educ^2

Source

https://www.cengage.com/cgi-wadsworth/course_products_wp.pl?fid=M20b&product_isbn_issn=9781111531041

Examples

 str(alcohol)
--

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

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How To Perform Statistical Analysis with Picostat
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  2. Near the top of the page there will be two drop downs. One for analysis and one for education. Here we will choose Analyis. Choose from one of the following:
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      1. Arithmetic mean
      2. Median
      3. Quartiles
      4. Minimum and Maximum
      5. Stem-and-leaf plot
      6. Standard deviation and Variance
      7. IQR
      8. Cumulative frequencies
    • Plot - a plot of two columns on the cartesian coordinate system
    • Boxplot - a Boxplot (box-and-whisker plot) of a column.
    • Correlation Coefficient - Compute the correlation coefficient between two columns.
    • Cumulative Frequency Histogram - Display a cumulative frequency histogram
    • Dotplot
    • Hollow Histogram - Plot two columns on the same histogram with a different color for each column.
    • Pie Chart
    • Regression - Perform a simple linear regression and compute the p-value and regression line. Also plots the data with the regression line.
    • Stem and Leaf Plots - Plot a one or two-sided stem-and-leaf plot from one or two columns respectively.
    • Visual Summaries - plots the following:
      1. Frequency Histogram
      2. Relative Frequency Histogram
      3. Cumulative Frequency Histogram
      4. Boxplot (Box-and-whisker plot)
      5. Dotplot
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