Part (i)
2 marks
The points do not lie close to a straight line — they curve upwards more and more steeply as increases, bending away from any single straight line through them. This suggests the relationship between and is not well modelled by ; a curved (non-linear) model fits the pattern of the data better.
Part (ii)
6 marksApproach
to compare the two proposed models, and , we compute the product moment correlation coefficient (PMCC) for each — the first between and , the second between and (since is linear in , not in ) — and take the model whose is closer to .
By GC,
Explanation: is closer to than , so gives a stronger linear relationship (between and ) than does (between and ), and is therefore the better model.
By GC, the regression line of on is
is the better model, with and , both correct to 3 s.f.
Part (iii)
2 marksUsing the equation from (ii), we solve for when :
taking the positive root since speed .
Explanation: lies within the range of the given data (), so this is an interpolation, and the estimate is reliable.
the estimated speed is (3 s.f.), and this estimate is reliable.
Part (iv)
2 marksUsing the equation from (ii), at ,
Explanation: lies outside the range of the given data (), so this is an extrapolation, and the estimate is unreliable — the equation is not known to hold below .
the estimated power used is (3 s.f.), but this estimate is unreliable since it extrapolates beyond the data.
Part (v)
Approach
the equation in (ii) uses in revolutions per minute. If denotes the speed in revolutions per second, then (there are seconds in a minute), so we substitute into the equation from (ii).
Let be the fan speed in revolutions per second, so . Substituting into from (ii),
By GC, (3 s.f.).
, correct to 3 s.f., where is the fan speed in revolutions per second.