*Freakonomics*and have been recently loving the illustrated version of

*Superfreakonomics*.

The authors have made statistical methods interesting by way of the content under study. Does a prostitute do better to work with a pimp or solo? What data and measures would we need to understand this? Reading this I was struck by three things:

- The
*relevance*upon which we place such import may really be a safer way to say*excitement*. Of course our lessons should be relevant, but only insomuch as they increase students' desire to learn. Balancing a checkbook is relevant but not interesting; detecting fraud in sumo wrestling scores is irrelevant but exciting. - The content and applications we present must be inherently exciting. We may feel that the Pythagorean Theorem is beautiful in and of itself, and we can do our best to convey that aspect, but we will fail half of our students if this is the extent to which we attempt to pique interest.
- Statistical methods are under-emphasized in high school, relative to their importance in the world. Decisions are being increasingly data-driven, and demand is high for competent analysts of all stripes. As much as I hate to admit it, statistics should probably supersede calculus in the effort to prepare students for the real world.

I do not think we need to teach students about the pros and cons of working with a pimp per se, but making our applications more surprising, varied, and spicy could draw in the students who would otherwise miss the point.

[...] Have the data come from something exciting in the first place (see Pimpact on student learning) [...]

ReplyDelete