Did That Treatment Actually Help You?

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A mistake we all make sometimes is attributing an improvement to whatever we've tried recently. For instance, we may get medicine from a doctor (or go to an acupuncturist) and feel better, so we conclude it worked. But did it actually work, or was it just chance? Here's a trick to help you decide: What matters (evidence-wise) is how likely that level of improvement would have been in that time period if the treatment works relative to how likely that improvement would have been if the treatm...
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How to run self-experiments to improve your life

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Written: March 24, 2018 | Released: May 28, 2021 I suggest running experiments every month or two to find new ways to improve your life. The basic procedure is simple:(1) Think of something important you'd like to try to improve (e.g., your fitness, sleep, anxiety, dating life, friendships, productivity, happiness at work, etc.).(2) Come up with a few ideas for something safe you could start doing (or start doing differently) that you think may have a reasonable chance of substantially impro...
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Your Best and Worst Influence – a two-minute social thought experiment

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A simple 2-minute social thought experiment for you: Note: I highly recommend that you don't just read this list of steps, but instead, that you actually do them! Reading these steps will not give you any benefit, but doing them might! Step 1 - Think for a moment about the person who is the best influence on you, or the person in your life you don't see that much that you most admire the traits or actions of. Step 2 - Visualize something great this person did or said, or think of a ...
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Testing Too Many Hypotheses

For each dataset, there is a limit to what we can use that dataset to test. Using the standard p-value based methods of science, the more hypotheses we check against the data, the more likely it will be that some of these checks give inaccurate conclusions. And this presents a big problem for the way science is practiced. Let's take an example to illustrate the principle. Suppose that you have information about 1000 people selected at random from the U.S. adult population. Your dataset includ...
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