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Math lesson plan · 12th grade (Year 13 in England) · 60 minutes

Linear regression and correlation coefficient

Statistics and probability

CCSS HSS.ID.B.6CCSS HSS.ID.C.7CCSS HSS.ID.C.8

Objective and success criteria

Students will: Linear regression and correlation coefficient.

  • I can answer questions on today's skill on my own, without help.
  • I can explain each step and say why it works.
  • I can check my answer and spot a mistake.

Before and after

Needs first: Scatter graphs and correlation; Find the equation of a line

Leads to: Predict with a regression line and judge reliability

Materials: Squared paper for charts, Class survey data, Sticky notes for a live chart, Mini whiteboards and pens, Printed student sheet (below).

Warm-up · 6 min

  • Quick retrieval from earlier learning (Scatter graphs and correlation; Find the equation of a line). Students answer on mini whiteboards.
  • Show answers together and note who needs support in the main task.
  1. A line has slope 5 and crosses the y-axis at −5. Write its equation as y = … (type the right-hand side). → 5x-5Prompt: Use y = mx + b.
  2. A line has slope 5 and crosses the y-axis at −4. Write its equation as y = … (type the right-hand side). → 5x-4Prompt: Use y = mx + b.
  3. A line has slope 3 and crosses the y-axis at −4. Write its equation as y = … (type the right-hand side). → 3x-4Prompt: Use y = mx + b.

Hook · 6 min

  • Take a quick class survey (favorite fruit, travel to school) and ask what the results tell us.
  • Share the objective: Linear regression and correlation coefficient. Read the success criteria together.

I do: model it · 12 min

  • Work through the example out loud, saying why you do each step, not just what you do.
  • Example: A correlation coefficient is r = 0.02. How would you describe the correlation?
  • Step 1: r = 0.02: no linear correlation.
  • Answer: no linear correlation
  • Pause after each step and ask a student to say what comes next.

We do: guided practice · 12 min

  • Do these together. Students try each step on whiteboards before you reveal it.
  • Use the hints as prompts rather than giving the answer.
  1. A correlation coefficient is r = 0.95. How would you describe the correlation? (strong positive / strong negative / weak positive / weak negative / no linear correlation) → strong positivePrompt: The sign gives the direction.
  2. The regression line is ŷ = 1.5x + 18. A data point is (2, 26). What is its residual (actual − predicted)? → 5Prompt: Find the predicted value ŷ at this x.

You do: independent practice · 17 min

  • Students work on the student sheet. Circulate and check the first two answers of every student early.
  • Students who finish: write a question of their own for a partner, with the answer.

The 8 questions are on the student sheet below, with answers in the key.

Exit ticket · 7 min

  • Two questions on their own. Sort answers into got it / nearly / not yet to plan the next lesson.
  1. The regression line is ŷ = 4.5x + 23. A data point is (18, 100). What is its residual (actual − predicted)? → -4Prompt: Find the predicted value ŷ at this x.
  2. A correlation coefficient is r = −0.4. How would you describe the correlation? (strong positive / strong negative / weak positive / weak negative / no linear correlation) → weak negativePrompt: The sign gives the direction.

Watch out for

  • Forgetting to put data in order before finding the median.
  • Reading a bar's height wrongly when the scale goes up in 2s or 5s.

Support and stretch

Support

  • Review first: Scatter graphs and correlation.
  • Use concrete materials: squared paper for charts.
  • Give the first step of each question, or a partly worked example to finish.
  • Pair with a confident partner for the guided practice.

Stretch

  • Move on to: Predict with a regression line and judge reliability.
  • Explain a common mistake in writing and how to fix it.
  • Write a word problem that uses today's skill, then solve a partner's.

Homework and more practice

Free online practice with hints and printable worksheets for this skill: eurekami.com/math/grade-12.

Free lesson plan from eurekami.com/lesson-plan-builder

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Linear regression and correlation coefficient

Name

Date

Score/ 8

  1. Question 1

    A correlation coefficient is r = 0.95. How would you describe the correlation?

    • A. strong positive
    • B. strong negative
    • C. weak positive
    • D. weak negative
    • E. no linear correlation
  2. Question 2

    The regression line is ŷ = 4.5x + 18. A data point is (19, 99.5). What is its residual (actual − predicted)?

    Answer

  3. Question 3

    A correlation coefficient is r = 0.02. How would you describe the correlation?

    • A. strong positive
    • B. strong negative
    • C. weak positive
    • D. weak negative
    • E. no linear correlation
  4. Question 4

    The regression line is ŷ = 2x + 17. A data point is (15, 42). What is its residual (actual − predicted)?

    Answer

  5. Question 5

    A correlation coefficient is r = −0.4. How would you describe the correlation?

    • A. strong positive
    • B. strong negative
    • C. weak positive
    • D. weak negative
    • E. no linear correlation
  6. Question 6

    The regression line is Å· = 4x + 13. By how much does the predicted y change when x increases by 1?

    Answer

  7. Question 7

    The regression line is Å· = 3x + 18. By how much does the predicted y change when x increases by 1?

    Answer

  8. Question 8

    A correlation coefficient is r = −0.92. How would you describe the correlation?

    • A. strong positive
    • B. strong negative
    • C. weak positive
    • D. weak negative
    • E. no linear correlation

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Answer key: Linear regression and correlation coefficient

  1. 1. A. strong positive

  2. 2. -4

  3. 3. E. no linear correlation

  4. 4. -5

  5. 5. D. weak negative

  6. 6. 4

  7. 7. 3

  8. 8. B. strong negative