The correlation is inappropriate as a measure of association between two quantitative variables

(a) When different people measure the variables using different units.

(b) When the relationship is highly nonlinear.

(c) When the data points fall exactly on a straight line.

(d) When the slope of the prediction equation is 0 using nearly all the data, but a couple of outliers are extremely high on y at the high end of the x scale.

(e) When y tends to decrease as x increases.

(f) When we have data for the entire population rather than a sample.

(g) When the sample has a much narrower range of x-values than does the population.