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And another one

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hadley 2016-07-15 16:02:42 -05:00
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commit 2e3ee662c0
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variation.Rmd
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@ -683,7 +683,7 @@ Finally, we could spot outliers in our data by examining the residuals of the mo
```{r echo = FALSE, fig.width = 3, fig.show='hold'}
diamond_mod <- lm(y ~ x, data = diamonds3)
resids <- augment(diamond_mod)
resids <- broom::augment(diamond_mod)
ggplot(resids) +
geom_histogram(aes(x = .resid), binwidth = 0.1)