R Dataset / Package Ecdat / politicalKnowledge

On this R-data statistics page, you will find information about the politicalKnowledge data set which pertains to Political knowledge in the US and Europe . The politicalKnowledge data set is found in the Ecdat R package. You can load the politicalKnowledge data set in R by issuing the following command at the console data("politicalKnowledge"). This will load the data into a variable called politicalKnowledge. If R says the politicalKnowledge data set is not found, you can try installing the package by issuing this command install.packages("Ecdat") 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 politicalKnowledge R data set. The size of this file is about 521 bytes.

Political knowledge in the US and Europe

Description

Data from McChesney and Nichols (2010) on domestic and international knowledge in Denmark, Finland, the UK and the US among college graduates, people with some college, and roughly 12th grade only.

Usage

data(politicalKnowledge)

Format

A data.frame containing 12 columns and 4 rows.

country: a character vector of Denmark, Finland, UK, and US, being the four countries comparied in this data set.
DomesticKnowledge.hs, DomesticKnowledge.sc, DomesticKnowledge.c: percent correct answers to calibrated questions regarding knowledge of prominent items in domestic news in a survey of residents of the four countries among college graduates (ending ".c"), some college (".sc") and high school ("hs"). Source: McChesney and Nichols (2010, chapter 1, chart 8).
InternationalKnowledge.hs, InternationalKnowledge.sc, InternationalKnowledge.c: percent correct answers to calibrated questions regarding knowledge of prominent items in international news in a survey of residents of the four countries by education level as for DomesticKnowledge. Source: McChesney and Nichols (2010, chapter 1, chart 7).
PoliticalKnowledge.hs, PoliticalKnowledge.sc, PoliticalKnowledge.c: average of domestic and international knowledge
PublicMediaPerCapita: Per capital spending on public media in 2007 in US dollars from McChesney and Nichols (2010, chapter 4, chart 1)
PublicMediaRel2US: Spending on public media relative to the US, being PublicMediaPerCapita / PublicMediaPerCapita[4].

Author(s)

Spencer Graves

Source

Robert W. McChesney and John Nichols (2010) The Death and Life of American Journalism (Nation Books)

Examples

##
## 1. Combine first 2 rows 
##
data(politicalKnowledge)
pk <- politicalKnowledge[-1,]
pk[1, -1] <- ((politicalKnowledge[1, -1] + 
 politicalKnowledge[2, -1])/2)
pk[1, 'country'] <- 'DK-FI'##
## 2.plot
##
xlim <- range(pk[, 'PublicMediaPerCapita'])
ylim <- 100*range(pk[2:7])
text.cex <- 2# to label the lines 
(US.UK <- (pk[2, -1]+pk[3, -1])/2)#png('Knowledge v. public media.png')
op <- par(mar=c(5, 7, 4, 2)+.1)
plot(c(0, 110), 100*ylim, type='n', axes=FALSE,
 xlab='public media $ per capita',
 ylab='Political Knowledge\n(% of standard questions)',
 cex.lab=2)
axis(1, cex.axis=2)
axis(2, las=2, cex.axis=2)
with(pk, text(PublicMediaPerCapita, 100*PoliticalKnowledge.hs,
country, cex=text.cex, xpd=NA, 
col=c('forestgreen', 'orange', 'red')))
with(pk, text(PublicMediaPerCapita, 100*PoliticalKnowledge.sc,
country, cex=text.cex, xpd=NA, 
col=c('forestgreen', 'orange', 'red')))
with(pk, text(PublicMediaPerCapita, 100*PoliticalKnowledge.c,
country, cex=text.cex, xpd=NA, 
col=c('forestgreen', 'orange', 'red')))
with(pk, lines(PublicMediaPerCapita, 100*PoliticalKnowledge.hs,
 type='b', pch=' '))
with(pk, lines(PublicMediaPerCapita, 100*PoliticalKnowledge.sc,
 type='b', pch=' '))
with(pk, lines(PublicMediaPerCapita, 100*PoliticalKnowledge.c,
 type='b', pch=' '))
with(US.UK, text(PublicMediaPerCapita, 100*PoliticalKnowledge.hs,
 'High School\nor less', srt=37, cex=1.5))
with(US.UK, text(PublicMediaPerCapita, 100*PoliticalKnowledge.sc,
 'some\ncollege', srt=10.5, cex=1.5))
with(US.UK, text(PublicMediaPerCapita, 100*PoliticalKnowledge.c,
 "Bachelor's\nor more", srt=-1, cex=1.5))par(op)
#dev.off()##
## redo for Wikimedia commons
## without English axis labels 
## to facilitate multilingual use 
##
#svg('Knowledge v. public media.svg')
op <- par(mar=c(3,3,2,2)+.1)
plot(c(0, 110), 100*ylim, type='n', axes=FALSE,
 xlab='', ylab='', cex.lab=2)
axis(1, cex.axis=2)
axis(2, las=2, cex.axis=2)
with(pk, text(PublicMediaPerCapita, 100*PoliticalKnowledge.hs,
country, cex=text.cex, xpd=NA, 
col=c('forestgreen', 'orange', 'red')))
with(pk, text(PublicMediaPerCapita, 100*PoliticalKnowledge.sc,
country, cex=text.cex, xpd=NA, 
col=c('forestgreen', 'orange', 'red')))
with(pk, text(PublicMediaPerCapita, 100*PoliticalKnowledge.c,
country, cex=text.cex, xpd=NA, 
col=c('forestgreen', 'orange', 'red')))
with(pk, lines(PublicMediaPerCapita, 100*PoliticalKnowledge.hs,
 type='b', pch=' '))
with(pk, lines(PublicMediaPerCapita, 100*PoliticalKnowledge.sc,
 type='b', pch=' '))
with(pk, lines(PublicMediaPerCapita, 100*PoliticalKnowledge.c,
 type='b', pch=' '))
par(op)
#dev.off()

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

Attachments: csv, json

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