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Product moment correlation coefficientEdexcel International A Level Maths: Subtopic test

10 questions, 27 marks

Edexcel International A Level Maths

Product moment correlation coefficient

Total 27 marks

Name

Class

Date

  1. 1
    A dealer records the age, xx years, and the value, yy thousand pounds, of 10 used cars of the same model. The summary statistics are Sxx=40S_{xx}=40, Syy=90S_{yy}=90 and Sxy=−48S_{xy}=-48.
    (a)
    Find the value of the product moment correlation coefficient, rr.
    [1 mark]
    • A−1.2-1.2
    • B0.80.8
    • C−0.8-0.8
    • D−0.533-0.533
    (b)
    Which statement best interprets this value?
    [1 mark]
    • AThere is strong negative linear correlation: older cars tend to have lower values
    • B80% of the cars lose value as they get older
    • CThere is weak negative linear correlation between age and value
    • DThere is strong positive linear correlation between age and value
    (c)
    The dealer converts the ages into months and the values into pounds. State the new value of rr and justify your answer.
    [2 marks]

    Total for question 1: 4 marks

  2. 2
    A seaside town records, for each of 12 months, the ice cream sales, xx hundred cones, and the number of sunburn cases, yy, treated at the local clinic. The product moment correlation coefficient for these data is r=0.91r=0.91.
    (a)
    Which statement correctly describes the correlation?
    [1 mark]
    • A91% of ice cream sales lead to sunburn cases
    • BThere is weak positive linear correlation between ice cream sales and sunburn cases
    • CThere is strong negative linear correlation between ice cream sales and sunburn cases
    • DThere is strong positive linear correlation between ice cream sales and sunburn cases
    (b)
    Which is the most appropriate conclusion?
    [1 mark]
    • AEating ice cream causes sunburn
    • BMonths with higher ice cream sales tend to have more sunburn cases, but this does not show that one causes the other
    • CSunburn causes people to buy ice cream
    • DA strong correlation shows that no other variable is involved
    (c)
    Suggest a reason why the two variables are strongly correlated, even though neither is likely to cause the other.
    [2 marks]

    Total for question 2: 4 marks

  3. 3
    A teacher records the number of practice tests, xx, completed by five students and their scores, yy, out of 5 in a final quiz. The values of xx are 1, 2, 3, 4, 5 and the scores are 2, 4, 5, 4, 5. For these data ∑x=15\sum x=15, ∑y=20\sum y=20, ∑x2=55\sum x^2=55, ∑y2=86\sum y^2=86 and ∑xy=66\sum xy=66.
    (a)
    Find SxxS_{xx}, SyyS_{yy} and SxyS_{xy}.
    [3 marks]
    (b)
    (i) Calculate the product moment correlation coefficient.
    (ii) Interpret your value in context.

    (iii) The teacher concludes that completing more practice tests causes the scores to rise. Comment on this conclusion.
    [4 marks]

    Total for question 3: 7 marks

  4. 4
    A researcher records the age, xx years, and the resale price, yy pounds, of eight laptops. The values of xx are 1, 2, 3, 4, 5, 6, 7, 8 and the prices are 900, 780, 700, 560, 520, 410, 330, 250. For these data ∑x=36\sum x=36, ∑y=4450\sum y=4450, ∑x2=204\sum x^2=204, ∑y2=2831900\sum y^2=2831900 and ∑xy=16170\sum xy=16170.
    (a)
    (i) Find SxxS_{xx}, SyyS_{yy} and SxyS_{xy}.
    (ii) Calculate the product moment correlation coefficient.

    (iii) Interpret your value in context.
    [6 marks]
    (b)
    (i) The researcher converts the ages into months and the prices into euros using a fixed exchange rate. State the new value of rr and give a reason.
    (ii) A ninth laptop, a rare model aged 12 years, is added to the data with a price of 1200 pounds. Without calculating, state and explain the effect on
    rr.
    (iii) For a different set of laptops, prices follow the curve
    y=1000xy=\frac{1000}{x} exactly. Explain why rr would not be −1-1.
    [6 marks]

    Total for question 4: 12 marks

End of questions

Written by the Exaim team, led by Shaun Daswani (Head of Upper Secondary, Improve ME Institute; MSc Financial Mathematics, Imperial College London; BSc, UCL) and Jason Daswani (operational lead, Improve ME Institute; LSE).