Please answer all parts of the question. No need to show work.

A Biology student who created a regression model to use a bird's Height when perched for predicting its Wingspan made the following two statements. Assuming the calculations were done correctly, explain what is wrong with each interpretation. a) My R of 93% shows that this linear model is appropriate. b) A bird 10 inches tall will have a wingspan of 17 inches. a) What is wrong with the statement "My R" of 93% shows that this linear model is appropriate"? A. The value of R" does not tell whether the model is appropriate, but measures the strength of the linear relationship. A scattered residual plot is the indicator of an appropriate model. B. A value of 93% is not a large enough value of R" to ensure that the linear model is appropriate. The required value for R is 95%. C. The value of R" represents the probability that a data point does not fit the linear model, a large R" means that most points don't fit the model and the model is not appropriate. D. There is nothing wrong with the statement, an R" value of 93% shows that this linear model is appropriate. b) What is wrong with the statement "A bird 10 inches tall will have a wingspan of 17 inches"? O A. The variables Height and Wingspan should not be using the same units (inches). O B. Predictions based on a regression line are for average values of y for a given x. The actual wingspan will vary around the prediction. O C. This linear model is meant to predict Height using Wingspan, and appropriate statement would be "A bird with a wingspan of 17 inches will have a height of 10 inches." O D. There is nothing wrong with the statement, assuming all calculations are correct, a bird 10 inches tall will have a wingspan of 17 inches