Scientists want true positives. They are known as “discoveries” and can win you things like Nobel Prizes, smooches from your romantic partner, and continued funding.
True negatives are less fun. They’re like thinking you’d tidied the house and done the laundry, only to realize that, nope, that was just in your head. You’d rather know the truth, but you wish it were otherwise.
By contrast, false negatives are haunting. They’re like looking for your lost keys in the right place but somehow not seeing them. You’ll never know how close you were.
Last is the scariest category of all: false positives. They are, in a word, “flukes,” falsehoods that, on a good hair day, pass for truths. They wreak havoc on science, sitting undetected in the research literature for years and spawning waste-of-time follow-ups. In science’s never-ending quest for truth, it’s impossible to avoid false positives altogether—but it’s crucial to keep them to a minimum.
That’s where the p-value comes in. Its whole purpose is to filter out flukes.
