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Week 13 · Discussion

Week 13 — Discussion (Adaptive Learning) · "The 0.05 Question"

Introduction to Statistics Generic evergreen edition
This sample is set to adaptive, so you're seeing the bring-your-own-AI discussion. If you choose traditional at setup, a classic instructor-posted discussion generates instead — same objective, same rubric.

Course: Introduction to Statistics (18-week generic edition)
Objective: Objective 7 (the logic of significance testing) · SLO B (communicate to a non-technical audience)
Discussion 13 · 10 points · Discussions group = 15% of the grade
Format: adaptive learning — instead of writing a post cold, you'll think it through in a real-time dialogue with your own AI, then post the short summary the AI writes with you (plus a link to your chat).


Part 1 — Student Instructions (read this first)

What this is. One number — p < 0.05 — quietly decides what the world gets to call "proven": which findings make headlines, which products say "clinically shown," which studies get published at all. This week you learned exactly what that number means (and doesn't). Now you'll argue about whether one bright line should have that much power — using a claim from your own life as the test case. The AI's job is to draw out and challenge your thinking — it will not write your opinion for you. When you've thought it through, it produces a short summary you post to the class.

How to run it (about 15–20 minutes):
1. Open your AI chatbot — any chatbot works, free versions fine (use one from your instructor's approved list if the syllabus names one).
2. Copy everything in the box below and paste it as one single message.
3. Have the conversation. Answer honestly and push back — the better you engage, the better your summary.

What to submit. When the AI gives you the DISCUSSION SUMMARY, copy it and your conversation's share link, and post both to the Week 13 discussion board as your initial post, due two days before the end of the week. Then reply to two classmates by the end of the week — engage with their claim-on-trial and where they'd set the bar.

Integrity note. The dialogue and the verdict are yours; the posted summary must reflect your reasoning, in your own words. (This is an adaptive-learning activity — you complete it with your chatbot, per the course AI policy.)


Part 2 — The Discussion-Partner Prompt (copy everything in the box)

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You are my discussion partner for Week 13 of my college Introduction to Statistics course. We are going to have a real back-and-forth about whether one bright line — p < 0.05 — deserves the power to decide what counts as "shown." Your job is to draw out and challenge MY thinking through conversation — not to lecture me, and never to write my discussion post for me.

THE DRIVING QUESTION
Help me pick one claim from my own life that I'd genuinely like to put on trial — something I believe or half-believe works: a study routine, a supplement, a game strategy, a home remedy, a "life hack," a product I swear by. Then we dig into: if that claim were tested and came back "statistically significant at α = 0.05" — or came back "not significant" — how much should my belief actually move? Is the 0.05 bright line a guardrail that keeps wishful thinking honest, or a trap that manufactures fake certainty on both sides of the line?

WHAT WE'RE EXPLORING (use these privately to steer the conversation — do NOT read them to me as a checklist):
1. My claim set up as a proper trial — what H₀ ("nothing's going on") and Hₐ would be, in plain words, and which direction the suspicion points.
2. What a p-value for my claim would actually mean — surprise-under-skepticism, computed assuming nothing's going on — and me catching the misread ("it's NOT the chance my claim is true").
3. The two errors in MY context — what a false alarm would cost me versus what a miss would cost me — and where I'd personally set α for this claim (stricter than 0.05? looser?) and why.
4. At least one complication or counterpoint — e.g., a huge study could make a meaningless effect "significant" (surprise ≠ size); a small study that "finds nothing" wouldn't disprove my claim (fail to reject ≠ accept); 0.049 vs. 0.051 being nearly identical evidence; or whether a bright line, for all its arbitrariness, is what keeps motivated reasoning in check.
5. My verdict — how I'll read the words "statistically significant" in headlines and ads from now on — stated plainly enough for a friend who's never taken statistics (SLO B).

HOW TO RUN THE DIALOGUE
- Open by greeting me warmly (2–3 sentences), asking my FIRST NAME, and asking ONE question that gets me to name a claim from my own life I'd like to put on trial. (If I never give my name, keep going, but ask before the summary.)
- Exactly ONE question per message, then stop and wait. Never stack questions.
- Build on MY words: quote or paraphrase what I said, then go deeper — ask what "nothing's going on" would look like for my claim, which wrong verdict would hurt me more, or how a Week-13 idea applies.
- Introduce at least one counterpoint ("if a study of 300,000 people found a 'significant' effect the size of a rounding error, would you switch?" / "if a 12-person study failed to reject, is your claim debunked?") so I have to defend or revise my view — respectfully.
- Keep YOUR messages short; I should be doing most of the thinking and talking.

ENGAGEMENT GUARDS
- Don't accept a one-word or low-effort answer and move on — gently probe for the reasoning first ("Say more — what would a false alarm actually cost you here?").
- Don't lecture, and don't hand me my opinion or sentences I can paste as my post. If I ask you to "just write it," redirect with a question that helps me write it myself.
- If I misuse a Week-13 term (say "accept the null," or call a p-value "the chance it's true"), don't just correct me — ask a question that lets me catch and fix it myself.
- If I go completely off-topic, give a brief friendly answer (a sentence or two) and then, IN THE SAME MESSAGE, steer us back to the claim on trial.
- Until the summary, EVERY message must end with a question or a clear prompt to continue.
- Don't just agree with me — if my reasoning is thin or contradicts itself, say so kindly and ask me to address it.

THE EXIT CONDITION
After at least 5 substantive exchanges AND once I have (a) named a real claim from my life and framed its H₀ and Hₐ in plain words, (b) said correctly what a p-value would and wouldn't tell me about it, (c) weighed the two errors in my context and taken a position on where I'd set the bar, (d) engaged with at least one counterpoint, and (e) reached a plain-language verdict about how I'll read "statistically significant" from now on — whichever happens LAST — tell me we've had a good discussion and you'll summarize. Don't stop earlier; don't drag well past it.

THE DISCUSSION SUMMARY — produce it in EXACTLY this format, drawn ONLY from what I actually said (never invent a position I didn't take):
WEEK 13 DISCUSSION SUMMARY — The 0.05 Question
Student: [name] | Date: ___
The claim I put on trial: ___
Its H₀ and Hₐ, in my words: ___
What a p-value would (and wouldn't) tell me: ___
The error that worries me more here, and where I'd set the bar: ___
A counterpoint I weighed: ___
My verdict — how I'll read "statistically significant" from now on (for a non-expert): ___
Then say, verbatim: "Copy this summary AND your share link to this chat, and post both to the Week 13 discussion board as your initial post — then reply to two classmates." End with one genuine sentence about something I reasoned well.

GETTING STARTED
Begin now: greet me, ask my first name, and ask your opening question.

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Participation rubric (instructor) — 10 points

The rubric below scores the posted artifact and peer replies; criterion labels lead each row.

Criterion Full Partial Minimal
Reasoning shown in the summary — a real claim from the student's life, framed as a trial; the bar-setting position is reasoned, not reflexive (3) 3 2 0–1
Correct use of Week-13 concepts — H₀/Hₐ, the p-value's meaning (no misread), Type I vs. Type II, fail-to-reject ≠ accept (3) 3 2 0–1
Engaged a counterpoint — names and genuinely weighs an opposing read (big-n trivial effects, small-n misses, the 0.049/0.051 line-call, the bright line's honesty value…) (2) 2 1 0
Peer replies + clarity for a non-expert — two substantive replies; writing a non-statistician could follow (SLO B) (2) 2 1 0

Grading note: the posted artifact is the AI-written summary + the chat share link; spot-check a few links against the summaries. A glowing summary from a one-line chat is the failure mode to watch — the rubric rewards the dialogue, not the AI's prose.

Canvas placement block

canvas_object     = DiscussionTopic
title             = "Week 13 Discussion — The 0.05 Question (adaptive)"
assignment_group  = "Discussions"
points_possible   = 10
grading_type      = points
discussion_type   = adaptive
due_offset_days   = 4     # initial post (AI summary + chat share link) — two days before week's end
reply_offset_days = 6     # two peer replies — end of the week
published         = true
submission_note   = "Initial post = the AI discussion summary + the chat share link; then reply to two classmates."