Business statistician Kaiser Fung just came out with another book, this one full of stories about how organizations use data:
1. Why do law school deans send each other junk mail?
2. Can a new statistic make us less fat?
3. How can sellouts ruin a business?
4. Will personalizing deals save Groupon?
5. Why do marketers send you mixed messages?
6. Are they new jobs if no one can apply?
7. How much did you pay for the eggs?
8. Are you a better coach or manager?
Unlike most books of this sort, there’s no hero: These are not stories about a fabulous businessman who made millions of dollars by following his dream and taking the customer seriously, nor are they Gladwellian sagas of brilliant scientists, nor are they auto-Gladwellian tales of the Ariely variety. In some ways, the stories in Fung’s book have the form of opened-up business reporting, in which you get to see the statistical models underlying various assumptions and conclusions. In that sense, this book could be a good way for people to learn some fundamental statistical concepts. The next step will be to fold such ideas into statistics (or “data science”) classes. As it is, our examples seem to oscillate between happytalk success stories (with a pretty regression model or a comfortably statistically-significant conclusion) or stories of selection bias, with no good integration into the how-to-do-it material. I tried to put this all together the last time I taught intro stat, but it didn’t work so well.