Answer: although the question is incomplete, but from the details i got online, am able to give this answer.
A linear model is suitable. The regression relationship is thus ˆ
y= 0.511 + 0.159x where y = ridership and x = tourist numbers. Expected ridership if 10 million tourists visit is 2,101,000.The predicted ridership if there are no tourist at all is 511,000 though this prediction is out of sample and must be treated with caution as zero tourists is out of the data range used to form the model. The correlation coefficient is given by r=n∑XY-∑X∑Y/√[n∑X^2-(∑X)^2] [n∑Y^2-(∑Y)^2]
which equals 0.917 in this case. The R^2 = r^2 = 0.84.
