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fixes minor spelling mistakes (#631)

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Jacob Kaplan
2018-06-20 05:03:40 -04:00
committed by Hadley Wickham
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model-many.Rmd
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@@ -15,7 +15,7 @@ In this chapter you're going to learn three powerful ideas that help you to work
because once you have tidy data, you can apply all of the techniques that
you've learned about earlier in the book.
We'll start by diving into a motivating example using data about life expectancy around the world. It's a small dataset but it illustrates how important modelling can be for improving your visualisations. We'll use a large number of simple models to partition out some of the strongest signal so we can see the subtler signals that remain. We'll also see how model summaries can help us pick out outliers and unusual trends.
We'll start by diving into a motivating example using data about life expectancy around the world. It's a small dataset but it illustrates how important modelling can be for improving your visualisations. We'll use a large number of simple models to partition out some of the strongest signals so we can see the subtler signals that remain. We'll also see how model summaries can help us pick out outliers and unusual trends.
The following sections will dive into more detail about the individual techniques: