The height (in feet) and volume (in cubic feet) of usable lumber of 32 cherry trees are measured by a researcher. The goal is to determine if volume of usable lumber can be estimated from the height of a tree.
If the data point \( (65,70) \) were removed from this study, how would the value of the correlation \( r \) change?
\( r \) would be smaller, because there are fewer data points.
\( r \) would be smaller, because this point falls in the pattern of the rest of the data.
\( r \) would be larger, because the \( x \) and \( y \) coordinates are larger than the mean \( x \) and mean \( y \), respectively.
\( r \) would be larger, because this point does not fall in the pattern of the rest of the data.
\( r \) would not change, because its value does not depend which variable is used for \( x \) and which is used for \( y \).