{
  "version": "1.2.0",
  "chapters": [
    {
      "title": "Intro & claim of the episode\r",
      "startTime": 0,
      "endTime": 60
    },
    {
      "title": "Why p-values matter in science\r",
      "startTime": 60,
      "endTime": 164
    },
    {
      "title": "What is a p-value? (ESP guessing game)\r",
      "startTime": 164,
      "endTime": 407
    },
    {
      "title": "Big vs. small p-values (psychic octopus example)\r",
      "startTime": 407,
      "endTime": 509
    },
    {
      "title": "Significance thresholds and the 0.05 rule\r",
      "startTime": 509,
      "endTime": 540
    },
    {
      "title": "Regina’s Nature paper on p-values\r",
      "startTime": 540,
      "endTime": 692
    },
    {
      "title": "Misconceptions about p-values\r",
      "startTime": 692,
      "endTime": 798
    },
    {
      "title": "Fisher vs. Neyman-Pearson (history & feud)\r",
      "startTime": 798,
      "endTime": 986
    },
    {
      "title": "Botox analogy and type I vs. type II errors\r",
      "startTime": 986,
      "endTime": 1181
    },
    {
      "title": "Dating app analogies for false positives/negatives\r",
      "startTime": 1181,
      "endTime": 1322
    },
    {
      "title": "How the 0.05 cutoff got enshrined\r",
      "startTime": 1322,
      "endTime": 1483.31
    },
    {
      "title": "Misinterpretations: statistical vs. practical significance\r",
      "startTime": 1483.31,
      "endTime": 1579.31
    },
    {
      "title": "Effect size, sample size, and “statistically discernible”\r",
      "startTime": 1579.31,
      "endTime": 1608.31
    },
    {
      "title": "P-hacking and researcher degrees of freedom\r",
      "startTime": 1608.31,
      "endTime": 1789.31
    },
    {
      "title": "Transparency, preregistration, and open science\r",
      "startTime": 1789.31,
      "endTime": 1855.31
    },
    {
      "title": "The 0.05 cutoff trap (p = 0.049 vs 0.051)\r",
      "startTime": 1855.31,
      "endTime": 1881.31
    },
    {
      "title": "The biggest misinterpretation: what p-values actually mean\r",
      "startTime": 1881.31,
      "endTime": 2012.31
    },
    {
      "title": "Paul the psychic octopus (worked example)\r",
      "startTime": 2012.31,
      "endTime": 2162.31
    },
    {
      "title": "Why Bayesian statistics differ\r",
      "startTime": 2162.31,
      "endTime": 2392.31
    },
    {
      "title": "Why aren’t we all Bayesian? (probability wars)\r",
      "startTime": 2392.31,
      "endTime": 2468.31
    },
    {
      "title": "The ASA p-value statement (behind the scenes)\r",
      "startTime": 2468.31,
      "endTime": 2599.31
    },
    {
      "title": "Key principles from the ASA white paper\r",
      "startTime": 2599.31,
      "endTime": 2658.31
    },
    {
      "title": "Wrapping up Regina’s paper\r",
      "startTime": 2658.31,
      "endTime": 2736.31
    },
    {
      "title": "Kristin’s paper on sports science (MBI)\r",
      "startTime": 2736.31,
      "endTime": 2893.31
    },
    {
      "title": "What MBI is and how it spread\r",
      "startTime": 2893.31,
      "endTime": 3046.31
    },
    {
      "title": "How Kristin got pulled in (Christie Aschwanden & FiveThirtyEight)\r",
      "startTime": 3046.31,
      "endTime": 3248.31
    },
    {
      "title": "Critiques of MBI and “Bayesian monster” rebuttal\r",
      "startTime": 3248.31,
      "endTime": 3377.31
    },
    {
      "title": "Spreadsheet autopsies (Welsh & Knight)\r",
      "startTime": 3377.31,
      "endTime": 3488.31
    },
    {
      "title": "Cherry juice example (why MBI misleads)\r",
      "startTime": 3488.31,
      "endTime": 3625.31
    },
    {
      "title": "Rebuttals and smoke & mirrors from MBI advocates\r",
      "startTime": 3625.31,
      "endTime": 3778.31
    },
    {
      "title": "Winner’s Curse and small samples\r",
      "startTime": 3778.31,
      "endTime": 3821.31
    },
    {
      "title": "Twitter fights & “establishment statistician”\r",
      "startTime": 3821.31,
      "endTime": 3959.31
    },
    {
      "title": "Cult-like following & Matrix red pill analogy\r",
      "startTime": 3959.31,
      "endTime": 4089.31
    },
    {
      "title": "Wrap-up",
      "startTime": 4089.31,
      "endTime": 4463
    }
  ]
}