| % File src/library/datasets/man/anscombe.Rd |
| % Part of the R package, https://www.R-project.org |
| % Copyright 1995-2018 R Core Team |
| % Distributed under GPL 2 or later |
| |
| \name{anscombe} |
| \docType{data} |
| \alias{anscombe} |
| \title{Anscombe's Quartet of \sQuote{Identical} Simple Linear Regressions} |
| \description{ |
| Four \eqn{x}-\eqn{y} datasets which have the same traditional |
| statistical properties (mean, variance, correlation, regression line, |
| etc.), yet are quite different. |
| } |
| \usage{anscombe} |
| \format{ |
| A data frame with 11 observations on 8 variables. |
| \tabular{rl}{ |
| x1 == x2 == x3 \tab the integers 4:14, specially arranged \cr |
| x4 \tab values 8 and 19 \cr |
| y1, y2, y3, y4 \tab numbers in (3, 12.5) with mean 7.5 and sdev 2.03} |
| } |
| \source{ |
| Tufte, Edward R. (1989). |
| \emph{The Visual Display of Quantitative Information}, 13--14. |
| Graphics Press. |
| } |
| \references{ |
| Anscombe, Francis J. (1973). |
| Graphs in statistical analysis. |
| \emph{The American Statistician}, \bold{27}, 17--21. |
| \doi{10.2307/2682899}. |
| |
| } |
| \examples{ |
| require(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) |
| } |
| \keyword{datasets} |