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Quantiles

Here, we'll continue with the Vocab dataset and use stat_quantile() to apply a quantile regression.

Linear regression predicts the mean response from the explanatory variables, quantile regression predicts a quantile response (e.g. the median) from the explanatory variables. Specific quantiles can be specified with the quantiles argument.

Specifying many quantiles and color your models according to year can make plots too busy. We'll explore ways of dealing with this in the next chapter.

This exercise is part of the course

Intermediate Data Visualization with ggplot2

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Hands-on interactive exercise

Have a go at this exercise by completing this sample code.

ggplot(Vocab, aes(x = education, y = vocabulary)) +
  geom_jitter(alpha = 0.25) +
  # Add a quantile stat, at 0.05, 0.5, and 0.95
  ___
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