R Dataset / Package Ecdat / incidents.byCountryYr
On this Picostat.com statistics page, you will find information about the incidents.byCountryYr data set which pertains to Global Terrorism Database yearly summaries. The incidents.byCountryYr data set is found in the Ecdat R package. Try to load the incidents.byCountryYr data set in R by issuing the following command at the console data("incidents.byCountryYr"). This may load the data into a variable called incidents.byCountryYr. If R says the incidents.byCountryYr 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 library("Ecdat") followed by data("incidents.byCountryYr"). 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 incidents.byCountryYr 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 incidents.byCountryYr R data set. The size of this file is about 22,611 bytes.
Global Terrorism Database yearly summaries
The Global Terrorism Database (GTD) "is a database of incidents of terrorism from 1970 onward". Through 2015, this database contains information on 141,966 incidents.
data(terrorism) data(incidents.byCountryYr) data(nkill.byCountryYr)
NOTE: For nkill.byCountryYr and for terrorism[c('nkill', 'nkill.us')], NAs in GTD were treated as 0. Thus the actual number of deaths were likely higher, unless this was more than offset by incidents being classified as terrorism, when they should not have been.
As noted with the "description" above, Pape et al. noted that the GTD reported an increase in suicide terrorism of over 70 percent between 2007 and 2013, while their Suicide Attack Database showed a 19 percent decrease over the same period. Pape et al. insisted that the most likely explanation for this difference is the change in the organization responsible for managing that data collection from ISVG to START.
If the issue is restricted to how incidents are classified as "suicide terrorism", this concern does not affect the other variables in this summary.
However, if it also impacts what incidents are classified as "terrorism", it suggests larger problems.
The Global Terrorism Database maintained by the National Consortium for the Study of Terrorism and Responses to Terrorism (START, 2015), downloaded 2015-11-28.
The world and US population figures came from "Total Population - Both Sexes", World Population Prospects 2015, published by the Population Division of the Department of Economic and Social Affairs of the United Nations, accessed 2016-09-05.
The World and US death rates came from the World Bank, accessed 2016-09-05.
Human Mortality Database. University of California, Berkeley (USA), and Max Planck Institute for Demographic Research (Germany).
Robert Pape, Keven Ruby, Vincent Bauer and Gentry Jenkins, "How to fix the flaws in the Global Terrorism Database and why it matters", The Washington Post, August 11, 2014 (accessed 2016-01-09).
data(terrorism) # plot deaths per million population plot(kill.pmp~year, terrorism, pch=method, type='b') plot(kill.pmp.us~year, terrorism, pch=method, type='b', log='y', las=1) # terrorism as parts per 10,000 # of all deaths plot(pkill*1e4~year, terrorism, pch=method, type='b', las=1) plot(pkill.us*1e4~year, terrorism, pch=method, type='b', log='y', las=1) # plot number of incidents, number killed, # and proportion NAplot(incidents~year, terrorism, type='b', pch=method)plot(nkill.us~year, terrorism, type='b', pch=method) plot(nkill.us~year, terrorism, type='b', pch=method, log='y')plot(pNA.nkill.us~year, terrorism, type='b', pch=method) abline(v=1997.5, lty='dotted', col='red') # by country by year data(incidents.byCountryYr) data(nkill.byCountryYr)yr <- as.integer(colnames( incidents.byCountryYr)) str(maxDeaths <- apply(nkill.byCountryYr, 1, max) ) str(omax <- order(maxDeaths, decreasing=TRUE)) head(maxDeaths[omax], 8) tolower(substring( names(maxDeaths[omax[1:8]]), 1, 2)) pch. <- c('i', 'g', 'f', 'l', 's', 'c', 'u', 'p') cols <- 1:4matplot(yr, sqrt(t( nkill.byCountryYr[omax[1:8], ])), type='b', pch=pch., axes=FALSE, ylab='(square root scale) ', xlab='', col=cols, main='number of terrorism deaths\nby country') axis(1) (max.nk <- max(nkill.byCountryYr[omax[1:8], ])) i.nk <- c(1, 100, 1000, 3000, 5000, 7000, 10000) cbind(i.nk, sqrt(i.nk)) axis(2, sqrt(i.nk), i.nk, las=1) ip <- paste(pch., names(maxDeaths[omax[1:8]])) legend('topleft', ip, cex=.55, col=cols, text.col=cols)
Dataset imported from https://www.r-project.org.
How To Register With a Username
How To Register With Google Single Sign On (SSO)
How To Login With a Username and Password
How To Login With Google Single Sign On (SSO)
How To Import a Dataset
How To Perform Statistical Analysis with Picostat
How To Use Educational Applications with Picostat
|Recent Queries For This Dataset|
No queries made on this dataset yet.
|Title||Authored on||Content type|
|R Dataset / Package wooldridge / driving||March 9, 2018 - 1:06 PM||Dataset|
|R Dataset / Package ISLR / College||March 9, 2018 - 1:06 PM||Dataset|
|R Dataset / Package Ecdat / Bwages||March 9, 2018 - 1:06 PM||Dataset|
|R Dataset / Package cluster / animals||March 9, 2018 - 1:06 PM||Dataset|
|R Dataset / Package Ecdat / Clothing||March 9, 2018 - 1:06 PM||Dataset|