# The Spearman Coefficient Of Correlation Case Study

2593 Words 11 Pages
Register to read the introduction… n=8 r= nxy-xynx2-x2×ny2-y2 = 8×2143.93 - 103.5×165.28×1356.85 - 103.52 × 8×3415.26 – 165.22 = 17151.44-17098.2142.55 × 31.04 =53.2466.52 = 0.8 The Spearman Coefficient of correlation

Year | Advertising (‘000) (x) | Sales (‘000) (y) | Rx | Ry | d | d2 | 2000 | 10.7 | 19.9 | 8 | 7 | 1 | 1 | 2001 | 11.1 | 19.8 | 7 | 8 | 1 | 1 | 2002 | 12.0 | 20.1 | 6 | 6 | 0 | 0 | 2003 | 12.6 | 20.7 | 5 | 4.5 | 0.5 | 0.25 | 2004 | 13.3 | 21.0 | 4 | 2 | 2 | 4 | 2005 | 14.5 | 22.1 | 3 | 1 | 2 | 4 | 2006 | 14.7 | 20.9 | 1 | 3 | 2 | 4 | 2007 | 14.6 | 20.7 | 2 | 4.5 | 2.5 | 6.25 | | | | | | | d2=20.5 |

n=8 R=1- 6d2+t3-t12nn2-1 = 1- 620.5+23-212882-1 = 1- 6 × 218 × 63
This method should be used for the future analysis to measure the sales from advertsing.

Question 3

Joycelyn works as an advertising manageress for a company which deals in stationery products through a nationwide chain of retail outlets. The company advertises mainly on local basis via newspapers, hoarding and exterior of buses. Josephine has been asked to assess the relationship between the amount spent on advertising and the corresponding level of sales achieved.

After a careful assessment she realizes that sales may be affected by other factors such as weather and households in each region the company operated. She added the number households to her data arguing that sales are expected to be higher in areas where there are more households. The data collected for each region is shown below: Region | Sales (£’000,000) | Advertising Expenditure (£’000,000) | Number of households (000) | A | 20 | 0.2 | 515 | B | 25 | 0.2 | 542 | C | 24 | 0.2 | 576 | D | 30 | 0.3 | 617 | E | 32 | 0.3 | 683 | F | 40 | 0.4 | 707 | G | 28 | 0.3 | 500 | H | 50 | 0.5 | 742 | I | 40 | 0.4 | 747 | J | 50 | 0.5 | 770

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