Analogical thinking is a powerful cognitive tool that leverages knowledge and<br>understanding of familiar ideas and relationships to form knowledge and understanding in a new<br>setting. For students approaching their first statistics class, fear of the unknown can be a major<br>factor in slowing and even stopping learning. Yet many statistical ideas have their roots in<br>thinking with which students are already familiar. Knowing this fact, and how to exploit it<br>through the use of analogy gives us a decisive advantage in the battle for hearts and minds of<br>students who do not yet know how much they need statistics in their lives. I will describe analogy<br>as a tool for teaching statistics, my experiences with its use, and many examples of analogies I<br>have invented, borrowed, stolen, lost then rediscovered, and otherwise acquired.
The CAUSE Research Group is supported in part by a member initiative grant from the American Statistical Association’s Section on Statistics and Data Science Education