S1 June 2013 Q1

EdexcelOld spec13 marksCorrelation & Regression

1. A meteorologist believes that there is a relationship between the height above sea level, \(h\) m, and the air temperature, \(t\) °C. Data is collected at the same time from 9 different places on the same mountain. The data is summarised in the table below.

\(h\)140011002608409005501230100770
\(t\)310209101352416

[You may assume that \(\sum h = 7150\), \(\sum t = 110\), \(\sum h^2 = 7\,171\,500\), \(\sum t^2 = 1716\), \(\sum th = 64\,980\) and \(\mathrm{S}_{tt} = 371.56\)]

(a) Calculate \(\mathrm{S}_{th}\) and \(\mathrm{S}_{hh}\). Give your answers to 3 significant figures. (3)
(b) Calculate the product moment correlation coefficient for this data. (2)
(c) State whether or not your value supports the use of a regression equation to predict the air temperature at different heights on this mountain. Give a reason for your answer. (1)
(d) Find the equation of the regression line of \(t\) on \(h\) giving your answer in the form \(t = a + bh\). (4)
(e) Interpret the value of \(b\). (1)
(f) Estimate the difference in air temperature between a height of 500 m and a height of 1000 m. (2)