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@@ -54,6 +54,13 @@ A good visualization will show you things you did not expect or raise new questi
 A good visualization might also hint that you're asking the wrong question or that you need to collect different data.
 Visualizations can surprise you, and they don't scale particularly well because they require a human to interpret them.
 
+**Models** are complementary tools to visualization.
+Once you have made your questions sufficiently precise, you can use a model to answer them.
+Models are a fundamentally mathematical or computational tool, so they generally scale well.
+Even when they don\'t, it\'s usually cheaper to buy more computers than it is to buy more brains!
+But every model makes assumptions, and by its very nature a model cannot question its own assumptions.
+That means a model cannot fundamentally surprise you.
+
 The last step of data science is **communication**, an absolutely critical part of any data analysis project.
 It doesn't matter how well your models and visualization have led you to understand the data unless you can also communicate your results to others.