{"id":"col-explain-p-values","audience":"college","category":"explaining","technique":"audience","title":"Get a stats idea explained with something you know","free":false,"task":"The Stats 200 slide on p-values lost you. You play intramural basketball, so you want the idea explained with a basketball example, in at most 4 sentences, plain text, with no formulas or math symbols. Stay with what the slide says, and don't repeat the misconception your professor warned about.","materialLabel":"The lecture slide and your notes (attached to your prompt automatically)","material":"STATS 200 - Lecture 9 slide: Hypothesis tests and p-values\n\nNull hypothesis (H0): nothing special is going on, no effect.\np-value = the probability of getting results at least as extreme as what you observed, IF H0 were true.\nSmall p (for example p < 0.05): the data would be surprising if H0 were true, so it counts as evidence against H0.\n\nWARNING - common misconception (it's on every exam!):\n- The p-value is NOT the probability that H0 is true.\n- A large p (p > 0.05) does NOT prove H0 is true. It just means the data isn't surprising under H0.\n\nSlide example: A coin is flipped 100 times and lands heads 62 times. If the coin were fair (H0), p is about 0.02.\n\nMy notes from class:\n- ??? so p = 0.02 means there's a 2% chance the coin is fair?\n- TA said the 0.05 cutoff is just a convention, people argue about it\n- prof talked about something called Bayesian stats at the end, said not on the exam\n- quiz on this next Tuesday\n\nMe: I get basketball, I play intramurals twice a week. I shoot about 70% from the free throw line.","rules":[{"type":"maxSentences","max":4},{"type":"plainText"}],"mistakes":[{"title":"Saying \"explain simply\"","why":"The AI picks its own example, usually coins or medicine, and still writes several paragraphs.","fix":"Give the length: \"at most 4 sentences.\"","checks":["maxSentences"]},{"title":"Not saying who it's for","why":"The AI doesn't know you play basketball, so it can't use an example that clicks for you.","fix":"Tell it: \"I play basketball. Use a free-throw example.\"","checks":["r0"]},{"title":"Repeating your confusion","why":"Your notes contain the classic mistake, and the AI may echo it back as if it were right.","fix":"Add: \"Don't say the p-value is the chance the null hypothesis is true.\"","checks":["r1"]},{"title":"Letting symbols creep in","why":"AI explanations of stats slide into notation like H0 and p < 0.05, which is what lost you.","fix":"Say: \"No formulas or math symbols, plain words only.\"","checks":["r2"]},{"title":"Bold terms and headings","why":"AI bolds key terms and adds headings, which you didn't need for 4 sentences.","fix":"Ask for \"plain text, no bold.\"","checks":["plainText"]}],"promptHints":[{"label":"Says who it's for","patterns":["basketball","free.?throw","i play"]},{"label":"Sets a sentence limit","patterns":["\\b([1-4]|two|three|four)\\b.{0,10}sentences?"]},{"label":"Rules out symbols","patterns":["no (formula|symbol|math|notation)","plain words"]},{"label":"Names the misconception","patterns":["misconception","not the (probability|chance)","chance.{0,30}true"]},{"label":"Stays with the slide","patterns":["slide","only.{0,20}(notes|material)"]}],"hint":"An explanation lands when it's built for one reader. Tell the AI what you already know well, how short to keep it, and which wrong idea to avoid.","rubricLabels":["Explains the idea through a basketball example (such as free throws or a shooting streak)","Never says or implies the p-value is the probability that the null hypothesis is true (for example, not 'a 2% chance the coin is fair' or 'a 2% chance the player is just average'), and does not say a large p-value proves nothing is going on","Uses no formulas or math symbols (such as H0, <, > or =), and adds nothing beyond the slide's ideas (no Bayesian stats, no debate about the 0.05 cutoff)"]}