In "Quantifying Real-Life Uncertainty," William Briggs, a statistician and contributor to the Broken Science Initiative, challenges the outdated methods traditionally used to teach statistics. Instead of relying on stale practices and rote memorization, Briggs introduces a more intuitive approach to understanding probability and statistics, minimizing busy work and emphasizing real understanding. Briggs has a Ph.D. in mathematical statistics from Cornell University and experience as a statistician at New York Methodist Hospital. He has witnessed firsthand the pitfalls in prediction and understanding uncertainty across various fields, from medicine to climatology. His main takeaway? Too many individuals have undue confidence in their beliefs

Law of Avgs Book by William Briggs

Summary:

In "Quantifying Real-Life Uncertainty," William Briggs, a statistician and contributor to the Broken Science Initiative, challenges the outdated methods traditionally used to teach statistics. Instead of relying on stale practices and rote memorization, Briggs introduces a more intuitive approach to understanding probability and statistics, minimizing busy work and emphasizing real understanding. Briggs has a Ph.D. in mathematical statistics from Cornell University and experience as a statistician at New York Methodist Hospital. He has witnessed firsthand the pitfalls in prediction and understanding uncertainty across various fields, from medicine to climatology. His main takeaway? Too many individuals have undue confidence in their beliefs

Law of Avgs Book by William Briggs

Summary:

In "Quantifying Real-Life Uncertainty," William Briggs, a statistician and contributor to the Broken Science Initiative, challenges the outdated methods traditionally used to teach statistics. Instead of relying on stale practices and rote memorization, Briggs introduces a more intuitive approach to understanding probability and statistics, minimizing busy work and emphasizing real understanding. Briggs has a Ph.D. in mathematical statistics from Cornell University and experience as a statistician at New York Methodist Hospital. He has witnessed firsthand the pitfalls in prediction and understanding uncertainty across various fields, from medicine to climatology. His main takeaway? Too many individuals have undue confidence in their beliefs.