Final answer:
The expected correlation between a basketball player's height and the number of trees in their neighborhood is no correlation. These variables are independent, and their relationship would be described by a correlation coefficient close to zero, signifying no meaningful relationship.
Step-by-step explanation:
The correlation one would expect between the height of a basketball player and the number of trees in his/her neighborhood is (c) No correlation. Correlation measures the strength and direction of a linear relationship between two quantitative variables. In this case, there's no logical reason to believe that a player's height is related to the arboreal density of their neighborhood. These variables are independent of each other. For example, while there is a positive correlation between height and weight, indicating that typically as height increases, weight also increases, no such relationship exists between a player's height and the number of trees. Described by a correlation coefficient close to zero, the scatterplot of these two variables would not show any discernible pattern.
Additionally, the correlation coefficient indicates the weakest relationship when it is closest to 0, strengthening as it moves towards -1 or 1, indicating a strong negative correlation or positive correlation, respectively.