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Date May 2015 Marks available 4 Reference code 15M.1.sl.TZ1.4
Level SL only Paper 1 Time zone TZ1
Command term Find Question number 4 Adapted from N/A

Question

Identical mosquito traps are placed at different distances from a lake. On one day the number of mosquitoes caught in 10 of the traps is recorded.

It is believed the number of mosquitoes caught varies linearly with the distance, in metres, of the trap from the lake.

Find

(i)     Pearson’s product–moment correlation coefficient, \(r\);

(ii)     the equation of the regression line \(y\) on \(x\).

[4]
a.

Use the equation of the regression line \(y\) on \(x\) to estimate the number of mosquitoes caught in a trap that is \(28\) m from the lake.

[2]
b.

Markscheme

(i)     \( - 0.998\;\;\;( - 0.997770 \ldots )\)     (A2)

Note: Award (A0)(A1) for \(0.998 (0.997770\ldots )\).

Award (A1)(A0) for \(- 0.997\).

 

(ii)     \(y =  - 0.470x + 81.7\;\;\;(y =  - 0.469713 \ldots x + 81.7279 \ldots )\)     (A1)(A1)     (C4)

Note: Award a maximum of (A0)(A1) if the answer is not an equation.

a.

\( - 0.469713 \ldots (28) + 81.7279\)     (M1)

Note: Award (M1) for correct substitution of \(28\) into their equation of regression line.

 

\( = 68.6{\text{ (mosquitoes)}}\;\;\;(68.5759 \ldots )\)     (A1)(ft)     (C2)

Note: Accept \(68\) or \(69\) or \(68.5(4)\) from use of \(3\) sf values.

Follow through from part (a)(ii).

b.

Examiners report

In part (a)(i), the majority of candidates knew how to calculate Pearson’s correlation coefficient using their GDC. The most common errors were incorrect rounding and omitting the – sign. In part (a)(ii) many candidates correctly found the equation of the regression line, again with rounding errors being the most common. A very common error was to use the second list as the frequency for the statistics.

a.

In part (b) substitution of 28 in the regression line was done correctly by many candidates. Candidates seemed to be well prepared for this type of question.

b.

Syllabus sections

Topic 4 - Statistical applications » 4.3 » The regression line for \(y \) on \(x \).
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