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## See how close they are (numerically!)
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## See how close they are (numerically!)
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sapply(mods, coef)
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sapply(mods, coef)
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lapply(mods, function(fm) coef(summary(fm)))
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lapply(mods, function(fm) coef(summary(fm)))
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## Now, do what you should have done in the first place: PLOTS
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## Now, do what you should have done in the first place: PLOTS
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op <- par(mfrow = c(2,2), mar = 0.1+c(4,4,1,1), oma =  c(0,0,2,0))
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op <- par(mfrow = c(2, 2), mar = 0.1+c(4,4,1,1), oma =  c(0, 0, 2, 0))
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for(i in 1:4) {
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for(i in 1:4) {
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  ff[2:3] <- lapply(paste0(c("y","x"), i), as.name)
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  ff[2:3] <- lapply(paste0(c("y","x"), i), as.name)
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  plot(ff, data = anscombe, col = "red", pch = 21, bg = "orange", cex = 1.2,
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  plot(ff, data = anscombe, col = "red", pch = 21, bg = "orange", cex = 1.2,
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       xlim = c(3,19), ylim = c(3,13))
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       xlim = c(3, 19), ylim = c(3, 13))
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  abline(mods[[i]], col = "blue")
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  abline(mods[[i]], col = "blue")
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}
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}
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mtext("Anscombe's 4 Regression data sets", outer = TRUE, cex = 1.5)
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mtext("Anscombe's 4 Regression data sets", outer = TRUE, cex = 1.5)
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par(op)
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par(op)
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}
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}