An urban planner is analyzing the market value of office rentals in a growing metropolitan area. He suspects that as the distance from the central business district increases, the average rental price per square meter decreases. He collects data from 8 randomly selected office blocks. The results for distance (D D\,D km) and rental price (P P\,P in £100s per m2^22) are shown in the table below:
| Office Block | A | B | C | D | E | F | G | H |
|---|---|---|---|---|---|---|---|---|
| Distance DDD (km) | 1.5 | 2.4 | 3.6 | 4.2 | 5.9 | 6.8 | 8.1 | 9.5 |
| Price PPP (£100s) | 94 | 82 | 88 | 70 | 75 | 60 | 52 | 48 |
Calculate Spearman's rank correlation coefficient for these data.
Stating your hypotheses clearly, test at the 5% level of significance whether there is evidence of a negative correlation between distance from the city center and office rental price. State the critical value used.
A developer claims that moving an existing office building 2 km closer to the city center will automatically increase its market value. Comment on this claim.