Allen Downey
Allen Downey is a curriculum designer at Brilliant.org and professor emeritus at Olin College.
He is the author of several books -- including Think Python, Think Bayes, and Probably Overthinking It -- and a blog about data science and Bayesian statistics. He received a Ph.D. in computer science from the University of California, Berkeley; and Bachelor's and Masters degrees from MIT.
Sessions
The fastest runners are much faster than we expect from a Gaussian distribution, and the best chess players are much better. In almost every field of human endeavor, there are outliers who stand out even among the most talented people in the world. Where do they come from?
In this talk, I present as possible explanations two data-generating processes that yield lognormal distributions, and show that these models describe many real-world scenarios in natural and social sciences, engineering, and business. And I suggest methods -- using SciPy tools -- for identifying these distributions, estimating their parameters, and generating predictions.