1. Gary compared the total attendance, at home matches and the total number of goals, scored x, y, at home during a season for each of 12 football teams playing in a league. He correctly calculated: = 1022500 = 130.9 = 8825 Sxx Syy Sxy (a) Calculate the product moment correlation coefficient for these data. (2) (b) Interpret the value of the correlation coefficient. (1) Helen was given the same data to analyse. In view of the large numbers involved she decided to divide the attendance figures by 100. She then calculated the product moment correlation coefficient between and y. (c) Write down the value Helen should have obtained. (1) (Total 4 marks) A company owns two petrol stations and along a main road. Total daily sales in the same 2. P Q week for (£p) and for (£q) are summarised in the table below. P Q p q Monday 4760 5380 Tuesday 5395 4460 Wednesday 5840 4640 Thursday 4650 5450 Friday 5365 4340 Saturday 4990 5550 Sunday 4365 5840 When these data are coded using = and = , x y = 48.1, = 52.8, = 486.44, = 613.22 and = 204.95. x y x2 y2 xy
1. Gary compared the total attendance, x, at home matches and the total number of goals, y, scored at home during a season for each of 12 football teams playing in a league. He correctly calculated: Sxx = 1022500 Syy = 130.9 Sxy = 8825 (a) Calculate the product moment correlation coefficient for these data. (2) (b) Interpret the value of the correlation coefficient. (1) Helen was given the same data to analyse. In view of the large numbers involved she decided to divide the attendance figures by 100. She then calculated the product moment correlation coefficient between and y. (c) Write down the value Helen should have obtained. (1) (Total 4 marks) 2. A company owns two petrol stations P and Q along a main road. Total daily sales in the same week for P (£p) and for Q (£q) are summarised in the table below. p q Monday 4760 5380 Tuesday 5395 4460 Wednesday 5840 4640 Thursday 4650 5450 Friday 5365 4340 Saturday 4990 5550 Sunday 4365 5840 When these data are coded using x = and y = , x = 48.1, y = 52.8, x2 = 486.44, y2 = 613.22 and xy = 204.95.
s1-coded-regression.docx