Complete · Technology
Bayesian Statistics
Why simple averages lie when one product has eighty ratings and another has five. A 2009 introduction to Bayesian thinking, from the Monty Hall problem to fairer product ratings.
- 01 Bayesian Statistics – Part I When one widget gets eighty ratings and another gets five, a simple average lies to you. Thomas Bayes, an 18th-century statistician, offers a way to weight those ratings fairly — the first in a short series on putting his method to work in marketing. Dec 8, 2009
- 02 Bayesian Statistics – Part II The Monty Hall problem drove me crazy through high school and college. Then a colleague introduced me to Bayesian statistics, which accounts for what the host knows, and why you should always switch doors. Dec 9, 2009
- 03 Bayesian Statistics – Part III A simple average breaks down when the room holds both small children and basketball players. How a Bayesian average makes product ratings comparable no matter how many people rated them — no statistics course required. Dec 10, 2009
- 04 Bayesian Statistics – Part IV Simple averages say drop Product C. Weighted averages say drop Product A. A Bayesian average says drop Product B. A case study in comparing product ratings across market segments, and why the method you choose changes the answer. Dec 11, 2009
- 05 Bayesian Statistics – Conclusion Most marketing decisions come down to numbers. Revisit yesterday's case study without assuming everyone rated every product, and Bayesian averages flip the result: the product that looked weakest turns out to be the highest rated. Dec 12, 2009
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