Week 4 Discussion — Moving Together, or Causing Each Other? — Traditional alternative (no AI)
Instructors: publish this instead of the adaptive version if you prefer, and unpublish or delete the adaptive one.
Hook
Headlines love a link: people who drink coffee live longer, students who sit in front earn better grades, towns with more bike lanes have fewer heart attacks. This week you learned to describe how two variables move together, and to ask the question every one of those headlines skips: is this association, or is it cause and effect?
Your discussion question — choose Option A or Option B; they carry the same weight and the same rubric, and you say which you picked.
Option A: Find a real claim — from the news, an ad, social media, your job, or a class — that two things are linked. Name the two variables and say whether each is quantitative or categorical. Would a scatterplot with a correlation or a two-way table with conditional distributions show the link? Then judge the claim: does it say "is associated with" or "causes," what lurking variable could explain the pattern, and what study would it take to settle cause and effect?
Option B: Pick two things you, your workplace, or your community actually measure that you suspect move together — hours of sleep and mood, temperature and sales, practice time and scores, anything. Predict the direction, form, and strength of the pattern, and say whether the correlation r would capture it or miss it. Then argue whether one would actually cause the other, and name the lurking variable most likely to fool you.
There is no single right answer here. A coffee headline, a sales chart at work, or your own sleep log can each be argued well in more than one direction. Pick one you actually care about, and tell us the story.
Expectations
Activity format: one initial post followed by two substantive peer replies. Plan on about 45 minutes across the two deadlines; your instructor sets both due dates in Canvas.
Your initial post — by the first due date (early in the module week):
- Say which option you chose.
- Name the two variables, say whether each is quantitative or categorical, and say which tool from this week would show their relationship.
- Use at least two of this week's terms (explanatory variable, response variable, scatterplot, direction, form, strength, correlation coefficient, marginal distribution, conditional distribution, association, causation, lurking variable, confounding variable) correctly.
- Give your association-or-causation judgment, with a reason, and name one specific lurking variable.
- Length: roughly 150–250 words if written. You may instead record your post as audio or video (about two minutes) and attach a transcript; both forms are scored by the same rubric.
Your replies — by the second due date (the end of the module week):
- Reply substantively to at least two classmates.
- A substantive reply does more than agree: suggest a lurking variable the poster missed, question whether the pattern would really be a straight line, or describe the experiment that could settle the cause. "Nice point!" on its own does not count.
What a strong post looks like:
I chose Option A. A post claims that students who sit in the front row earn higher grades. Seat row is categorical and grade is quantitative here, so I would compare the grade distributions for front-row and back-row students rather than compute a correlation. The claim implies cause, but the seating was chosen, not assigned. Motivation is a likely lurking variable: motivated students may choose the front and also study more. Only an experiment that randomly assigns seats could test whether the seat itself matters.
Notice how it names the variables and their types, picks a fitting tool, keeps association apart from causation, and names a specific lurking variable. That is the bar.
Participation rubric
This discussion is worth 10 points. The three criteria below look at your initial post and your peer replies.
| Criterion | Full credit | Partial credit | No credit |
|---|---|---|---|
| Quality of the initial post (4 pts) | A real, specific claim or pair of variables is described, the tool and expected pattern are explained, and the cause-or-association judgment is backed by a reason | A claim or pair is present, but the description is vague or the judgment is asserted without a reason | Missing, off-topic, or no reasoning about the relationship |
| Use of course concepts (3 pts) | Uses this week's terms precisely, keeping association separate from causation and naming a specific lurking variable | Uses a term loosely or with a small error | No course terms, or used incorrectly |
| Engagement with peers (3 pts) | Two or more substantive replies that extend or challenge a classmate's reasoning | One substantive reply, or replies that only agree | No replies, or "I agree" with nothing added |
Post early if you can — the best threads happen when people have time to reply before the second due date.
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