# anscombe {datasets}

Anscombe's Quartet of &lsquo;Identical&rsquo; Simple Linear Regressions
Package:
datasets
Version:
R 3.0.1

### Description

Four x-y datasets which have the same traditional statistical properties (mean, variance, correlation, regression line, etc.), yet are quite different.

### Usage

```anscombe
```

### References

Anscombe, Francis J. (1973) Graphs in statistical analysis. American Statistician, 27, 17--21.

### 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)```

Documentation reproduced from R 3.0.1. License: GPL-2.