A botanist found a correlation between the length of an aspen leaf and its surface area to be 0.94. Why does the correlation val
ue of 0.94 not necessarily indicate that a linear model is the most appropriate model for the relationship between length of an aspen leaf and its surface area?
A correlation coefficient of +1 or -1 will indicate a direct linear model is the most appropriate but 0.94 shows that a very good direct correlation exists between the length of an aspen leaf and its surface area.
Step-by-step explanation:
this is because a values of r lying between +1 and −1, where +1 indicates perfect direct correlation,−1 indicates perfect inverse correlation and 0 indicates that no correlation exists.
Between these values, the smaller the value of r, the less is the amount of correlation which exists. Generally, values of r in the ranges 0.7 to 1 and −0.7 to −1 show that a fair amount of correlation exists.
A correlation coefficient of 0.94 shows that a very good direct correlation exists between the length of an aspen leaf and its surface area but not necessarily indicate a linear model is the appropriate .