Statistics

Ever seen a headline like “Study Finds Chocolate Makes You Happier” and thought, finally, science gets something right? Congratulations, you already care about p-values. You just did not know that was the thing you were reacting to. Here is a smaller, less delicious version of the same question. You flip a coin ten times. Eight land on heads. Your friend says, immediately, “That coin must be weighted.” Another friend just shrugs. “Weird things happen sometimes.” So who is right? ...

We’ve already looked at how spread out data can be. This time, we’re going to look at something different: the shape of the data. Imagine Kiki is baking chocolate chip cookies. She follows the same recipe every time and tries to make every cookie exactly the same size. Of course, baking is never perfectly perfect. Some cookies come out a little bigger. Some are a little smaller. But most are very close to the size she was aiming for. ...

Linear function and linear regression sound alike but they do completely different jobs. One follows a rule. The other discovers one. And once you see the difference, a lot of data science starts to make sense. A Tale of Two Lines You and your friend both work part-time at a bubble tea shop. You get paid $15 per hour. Simple. After 3 hours you know you’ve earned $45. After 6 hours, $90. There’s a perfect formula. No surprises, no guessing. ...

You and your friend both average 8,000 steps a day. Same average. Same fitness goal. But your weeks look completely different. You walk about 7,800 to 8,200 steps every day. Some days are slightly higher, some slightly lower, but you are remarkably consistent. Your friend is the opposite. One day she walks 2,000 steps. The next she finishes a half marathon and records 18,000. A few days later she barely leaves the couch with 1,500, then cycles to work and reaches 14,000. ...

A simple look at why ‘average’ doesn’t always mean what you think it means.