typo in EDA.Rmd (#217)
which will come back to -> which we will come back to
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@ -130,7 +130,7 @@ ggplot(data = smaller, mapping = aes(x = carat, colour = cut)) +
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geom_freqpoly(binwidth = 0.1)
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```
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There are a few challenges with this type of plot, which will come back to in [visualisation a categorical and a continuous variable](#cat-cont).
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There are a few challenges with this type of plot, which we will come back to in [visualisation a categorical and a continuous variable](#cat-cont).
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Now that you can visualise variation, what should you look for in your plots? And what type of follow-up questions should you ask? I've put together a list below of the most useful types of information that you will find in your graphs, along with some follow up questions for each type of information. The key to asking good follow up questions will be to rely on your **curiosity** (What do you want to learn more about?) as well as your **skepticism** (How could this be misleading?).
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