# R Dataset / Package datasets / anscombe

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On this R-data statistics page, you will find information about the anscombe data set which pertains to Anscombe's Quartet of ‘Identical’ Simple Linear Regressions. The anscombe data set is found in the datasets R package. You can load the anscombe data set in R by issuing the following command at the console data("anscombe"). This will load the data into a variable called anscombe. If R says the anscombe data set is not found, you can try installing the package by issuing this command install.packages("datasets") 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 anscombe R data set. The size of this file is about 364 bytes. ## Anscombe's Quartet of ‘Identical’ Simple Linear Regressions## DescriptionFour ## Usageanscombe ## FormatA data frame with 11 observations on 8 variables.
## SourceTufte, Edward R. (1989) ## ReferencesAnscombe, Francis J. (1973) Graphs in statistical analysis. ## Examplesrequire(stats); require(graphics) summary(anscombe)##-- now some "magic" to do the 4 regressions in a loop: ff <- y ~ x mods <- setNames(as.list(1:4), paste0("lm", 1:4)) for(i in 1:4) { ff[2:3] <- lapply(paste0(c("y","x"), i), as.name) ## or ff[[2]] <- as.name(paste0("y", i)) ## ff[[3]] <- as.name(paste0("x", i)) mods[[i]] <- lmi <- lm(ff, data = anscombe) print(anova(lmi)) }## See how close they are (numerically!) sapply(mods, coef) lapply(mods, function(fm) coef(summary(fm)))## Now, do what you should have done in the first place: PLOTS op <- par(mfrow = c(2, 2), mar = 0.1+c(4,4,1,1), oma = c(0, 0, 2, 0)) for(i in 1:4) { ff[2:3] <- lapply(paste0(c("y","x"), i), as.name) plot(ff, data = anscombe, col = "red", pch = 21, bg = "orange", cex = 1.2, xlim = c(3, 19), ylim = c(3, 13)) abline(mods[[i]], col = "blue") } mtext("Anscombe's 4 Regression data sets", outer = TRUE, cex = 1.5) par(op) -- Dataset imported from https://www.r-project.org. |

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Attachment | Size |
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dataset-84646.csv | 364 bytes |