What's the Connection?
Students collect paired class data — arm span and height, study time and score — then build scatter plots and argue about which pairs are genuinely related.
Common Core standards covered
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Teacher-facing overview
Big idea: Construct and interpret scatter plots and describe patterns of association, including clustering, outliers, and linear or nonlinear association.
Student target: “I can construct a scatter plot from bivariate data and describe its association — direction, form, strength — including clusters and outliers.”
Success criteria: I can plot paired data with labeled, sensibly scaled axes. · I can describe an association as positive, negative, or none — and as linear or nonlinear. · I can spot an outlier and propose what might explain it before deleting anything. · I can explain why association is not proof of causation.
Essential question
Two measurements per person, one dot per person. What can a cloud of dots tell you that neither list could alone?
Learning target: I can construct a scatter plot from bivariate data and describe its association — direction, form, strength — including clusters and outliers.
Success criteria
- I can plot paired data with labeled, sensibly scaled axes.
- I can describe an association as positive, negative, or none — and as linear or nonlinear.
- I can spot an outlier and propose what might explain it before deleting anything.
- I can explain why association is not proof of causation.
Why this matters
The scatter plot is the first tool that lets data ARGUE: one glance answers 'do these travel together?' before any formula exists. Direction, form, strength, outliers — that vocabulary is the reading skill behind every trend chart in news, sports and science. And the guardrail matters as much as the tool: dots that travel together do not prove one causes the other, which is the single most-abused inference in public life.
Students should already be able to
- Plot points in the first quadrant.
- Read tables of paired values.
- Linear vs nonlinear from Streaming Growth Studio's difference test (informally).
Vocabulary to define explicitly
- Bivariate data
Two measurements per individual — each individual becomes one point (x, y).
Example: Each student contributes (hours studied, quiz score): one dot.
Not an example: A list of quiz scores alone is univariate — no pairing, no scatter plot.
🔒 4 more terms with examples and non-examples — Positive / negative association, Linear association, Outlier, Cluster — are defined in the full lesson. See plans →
Where this shows up outside the classroom
Assessment plan
Formative — for feedback during the lesson
- Warm-up votes: priors on record.
- Desk logs during plotting: the four-word discipline.
- Headline rulings: causal-verb detection in real time.
Summative — the graded evidence: The exit ticket (description, outlier, ruling), scored with the four-criterion rubric.
The task students work on
Your team is the school-paper data desk. Three data sets came in: study time vs quiz score for 12 students, shoe size vs quiz score for the same 12, and outdoor temperature vs hot-chocolate sales for 10 winter days. For each: build the scatter plot, describe the association in the desk's four words (direction, form, strength, outliers) — and decide which headlines the data can honestly support.
Data desk log — one row per data set.
| Data set | Direction | Form | Strength | Outliers / clusters |
|---|---|---|---|---|
| Study time vs score | ||||
| Shoe size vs score | ||||
| Temperature vs cocoa sales |
Anticipated student strategies
See the whole, judge the trend, then honor the exceptions. The outlier conversation goes last because it only makes sense once the pattern it violates is established.
- Plot, then squint. The student plots all pairs, steps back, and reads the cloud's tilt: up-together, down-together, or shapeless.
The intended workflow. Share first — and insist the squint happens AFTER all points are placed, not row by row.
🔒 2 more anticipated strategies with select-and-sequence guidance are in the full lesson. See plans →
Lesson script
Record the votes. Name the day's job: dots will confirm or embarrass these votes — and the desk vocabulary (direction, form, strength, outliers) is how the verdicts get written.
Listen for: A shapeless cloud — no tilt, no trend. Knowing x tells you nothing about y.
Then the outlier interview: sick on quiz day? studied the wrong unit? The point stays on the plot with a note. Close with the scale discipline: axes labeled with units, score axis marked in tens.
- Four words, every time: direction, form, strength, outliers.
- Outliers get interviewed, never silently deleted.
Listen for: No — it shows they travel together. Maybe strong students both study more AND score higher. Association is a lead, not a verdict.
🔒 The remaining 4 steps — fully scripted with teacher-says lines, discourse questions, look-fors, and interventions — are in the full lesson. See plans →
Misconceptions and how to respond
- “The dots travel together, so x causes y.” Ice cream and sunburn travel together — sunshine drives both. Association is a lead; causation needs an experiment.
- “An outlier is a mistake — delete it.” — the teacher response is in the full lesson.
- “Negative association means weak or bad.” — the teacher response is in the full lesson.
- “Connect the dots to show the trend.” — the teacher response is in the full lesson.
- “No trend means the plot failed.” — the teacher response is in the full lesson.
🔒 Every misconception ships with a tested classroom response. See plans →
Scaffolded practice
The workbook follows gradual release rather than a page of blank prompts: 1 fully worked, 1 partially completed, then 3 independent.
- I doDescribe the study-time scatter plot in the desk's four words.
🔒 4 more prompts across all three release tiers are in the full lesson. See plans →
Worked solutions and scaffolds for every prompt are in the downloadable kit, included with membership. See plans and pricing.
Exit ticket
- A scatter plot of car age vs resale value slopes steadily down with tight dots. Describe it in the four desk words.
🔒 2 more exit-ticket questions are in the full lesson. See plans →
Worked answers, the completed answer tables, and the scoring rubric are in the downloadable kit, included with membership. See plans and pricing.
Printable handouts in the kit
All handouts are in Printable_Handouts.pdf inside the kit download.
Materials and classroom resources
Student experience
Students enter through a low-floor prompt, build or sketch a model, test a strategy, revise their thinking, collaborate, and present a final solution. The task remains accessible while allowing for sophisticated reasoning.
Detailed facilitation notes
- Step 1: Collect two paired measurements from every student. Ask: “What do you notice?”, “What could you try next?”, and “How can you prove that?”
- Step 2: Teams build a scatter plot with clearly labeled and scaled axes. Ask: “What do you notice?”, “What could you try next?”, and “How can you prove that?”
- Step 3: Describe the association using direction, form, and strength. Ask: “What do you notice?”, “What could you try next?”, and “How can you prove that?”
- Step 4: Identify outliers and discuss what might explain them. Ask: “What do you notice?”, “What could you try next?”, and “How can you prove that?”
Differentiation and inclusion
Support: Supply pre-scaled axes for support; extend by comparing a linear and a clearly nonlinear data set.
Language support: “I started by…”, “My model shows…”, and “I know my answer is reasonable because…”.
Extension: Require a second solution, alter a condition, or have students write a challenge for another group.
Accessibility: Manipulatives, enlarged visuals, oral response choices, partner reading, and reduced-copy student pages.
Assessment plan
Formative checks: Strategy choice, accuracy, representation, collaboration, and explanation.
End evidence: Students describe the association in their scatter plot and justify whether an outlier should be investigated.
Mastery: The student completes the task accurately and explains the strategy with limited prompting.