Thanks, David. Thanks, David. My name is Max Froen. I'm a data strategist, and I'm really fascinated by how people make decisions with statistics. Good and bad. Something I love, and I want to share with you. In 2004, the drug giant Merck pulled the plug on Viox, a pain killer that was marketed for arthritis. But unlike Aspen or Elive, which prevent heart attacks, Viox caused them, and estimated 60,000 people worldwide died because of it. I want to convince you that those 60,000 died because many of us have come to rely on a certain kind of statistical test as a substitute for scientific reasoning. Statistics tools are great assets for critical thinking, but when they use mechanically as if they were oracles of truth, people die. So one of the first studies concerned the rate of Viox and stomach ulcers. And in this study, when I was published, there were four times as many heart attacks in patients taking Viox, 17 against four. So let me introduce the main antagonist in our story, no hypothesis significance testing, also known as significance testing, also known as statistical significance. It was developed in the 1930s as a tool intended to replace the judgment of a scientist with a single definitive test, and unfortunately, is a test with sugary limitations. If your problem has a simple yes-no answer, and all results are equally good or bad to you, and you have no prior information, it's a good tool. That's not how medicine or anything important actually works, and yet we regulated as if it did. So Merck and the authors of the study went out of their way to provide alternative explanations for the 4-21 heart attack ratio. Perhaps Elive had a bigger protective effect than realized, or there was a problem with experiment guidelines. These are both plausible if a little far fetched, but we do know, as they've ever moving questionable patients, the heart attack ratio dropped to 2-1, and now there were just too few heart attacks to pass statistical significance. We should be more willing to err on the side of caution when lives are at stake. A careful assessment of study evidence would show that the tradeoff was approximately one heart attack for every reduced ulcer. Would you take that trade? In 2000, there was a second study, this one more firmly controlled by Merck, also on the topic of viox and stomach ulcers. Court records from later patient lawsuits would show that there were eight heart attacks in patients taking a viox against one taking a leave. And because of the prior result, Merck started freaking out internally. Three heart attacks got reclassified to something else, bringing the total to 5 against 1, which now stripped of those exact 3 heart attacks, failed to pass statistical significance. But if we care about the magnitude of an effect, and not its existence, and we understand that a drug which causes heart attacks is worse than a drug which does not cause heart attacks. And we have prior information, even 5 against 1 should be setting off alarms. But it didn't. Without statistical significance, the FDA didn't feel compelled to tell Merck to pull viox off the shelf. A single number is not an argument. In a just world, in order for Merck to have the right to keep selling viox, this would have kicked off a furious round of study. But it didn't. So the viox debacle ends with one final study. Again, not about heart attacks. This one, checking to see if viox prevented colon polyps, took place over the course of three years, while the prior studies had lasted only three months. And in this one, there was a study statistician doing what you should do, exploring the data, testing ideas, being unguarded against hypotheses the study wasn't designed to test explicitly, and he was finding heart attacks. Two months before the study was to end, an independent monitoring panel ended early for safety reasons. And Merck pulled viox off the shelf. But even here, both parties waited for one to two years after the study was already indicating increased heart attack risk for the difference to reach statistical significance. And in the meantime, Merck was selling billions of dollars of viox per year. So what's it take away from this? Relying an absolute cutoffs makes us vulnerable to manipulation and tunnel vision. Statistics should be used as a tool for critically thinking about outcomes, not as a magic oracle that grants you the right to call something true. And now there are examples like this all over. In medicine, in the social sciences, in financial regulation, and maybe in your business or hobby, it doesn't take maliciousness to be fooled by statistical significance, just to desire to cling to the illusion of certainty. Now some scientists in the room may be cheering, and others may be fuming. To those of you who rely on significance to tell you what's right, I want to tell you your hammer is broken, and it's hurting all of us. I want to believe in magic as much as everyone else, but there's no such thing as a truth machine. Thank you. You