My top-10 most popular episodes of The Tim Ferriss Show, as of September 1, 2017, are below.
But achtung! I didn’t rank episodes in descending order of total downloads. Due to rapid growth, there would be a misleading recency bias — in other words, a newer decent episode could be “more popular” than an older blockbuster episode that was 3x the average at the time. To correct for this, we used a better methodology, and I owe special thanks to my brother for the help.*
1. Jamie Foxx on Workout Routines, Success Habits, and Untold Hollywood Stories (#124) — tim.blog/jamie
2. The Scariest Navy SEAL I’ve Ever Met . . . and What He Taught Me (#107) — tim.blog/jocko
3. Arnold Schwarzenegger on Psychological Warfare (and Much More) (#60) — tim.blog/arnold
4. Dom D’Agostino on Fasting, Ketosis, and the End of Cancer (#117) — tim.blog/dom2
5. Tony Robbins on Morning Routines, Peak Performance, and Mastering Money (#37) — tim.blog/tony
6. How to Design a Life — Debbie Millman (#214) — tim.blog/debbie
7. Tony Robbins — On Achievement Versus Fulfillment (#178) — tim.blog/tony2
8. Kevin Rose (#1) — tim.blog/kevinrose [If you want to hear how bad a first episode can be, this delivers. Drunkenness didn’t help matters.]
9. Charles Poliquin on Strength Training, Shredding Body Fat, and Increasing Testosterone and Sex Drive (#91) — tim.blog/charles
10. Mr. Money Mustache — Living Beautifully on $25–27K Per Year (#221) — tim.blog/mustache
*Explanation from my statistician brother: “I first modeled the growth of the podcast over time. I used a linear regression model after a logarithmic transformation. (A logarithmic transform, which implies that the downloads have been growing exponentially, was the near optimal box-cox transformation.) I calculated the standard error at each point using the 95 percent prediction bands. For each podcast episode, I then calculated the residual (the difference between the observed downloads and the regression line) and then standardized this difference by the standard error. I then ranked episodes according to this metric, by how many standard deviations they exceeded the mean trend line.”
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