A farmer is interested in predicting the weight (in grams) of a pumpkin based on its circumference (in centimeters). Measurements were obtained from a random sample of pumpkins, all of which had circumferences between 32 and 82 centimeters. The correlation between these variables was r = 0.79, and the regression equation turned out to be as follows:

Predicted weight = -2902.12 + 86.14(circumference)

Based on this information, which one of the following statements is correct?

Group of answer choices

If we switch the variables so that circumference is the response variable and weight is the explanatory variable, r will change.

The percentage of variability in pumpkin weight that cannot be explained by the regression equation is 37.59%.

If weight is measured in pounds instead of grams, r will change.

The predicted weight of a pumpkin with a circumference of 50 centimeters is 7209.12 grams.

If a pumpkin has a circumference of 40 centimeters, we would not want to use the regression equation to predict the pumpkin's weight since this would be considered extrapolation.

ANSWER ONLY PLEASE!