The following data was collected for seven cars, showing their engine size, \(x\) litres, and their fuel consumption, \(y\) km per litre, on a long journey.
| Car | \(A\) | \(B\) | \(C\) | \(D\) | \(E\) | \(F\) | \(G\) |
| \(x\) | 0.95 | 1.20 | 1.37 | 1.76 | 2.25 | 2.50 | 2.875 |
| \(y\) | 21.3 | 17.2 | 15.5 | 19.1 | 14.7 | 11.4 | 9.0 |
\(\sum x = 12.905\), \(\sum x^2 = 26.8951\), \(\sum y = 108.2\), \(\sum y^2 = 1781.64\), \(\sum xy = 183.176\).
- Calculate the equation of the regression line of \(x\) on \(y\), expressing your answer in the form \(x = ay + b\). [6 marks]
- Calculate the product moment correlation coefficient between \(y\) and \(x\) and give a brief interpretation of its value. [4 marks]
- Use the equation of the regression line to estimate the value of \(x\) when \(y = 12\). State, with a reason, how accurate you would expect this estimate to be. [3 marks]
- Comment on the use of the line to find values of \(x\) as \(y\) gets very small. [2 marks]