Brandon works as a statistician for the Toronto Blue Jays, and wants to analyze the relationship between a pitcher's age and how many strikeouts they accumulate in a season. He takes a sample of 6 Blue Jays pitchers with ages between 25 and 34 and finds there is a linear relationship between their ages and the number of strikeouts they had in the 2015 season. Here are the numerical summaries for age and the number of strikeouts: r=0.6,age=27.9,sage=3.07,strikeout=108.4,sstrikeout=7.14r=0.6,age=27.9,sage=3.07,strikeout=108.4,sstrikeout=7.14 (a) What is the value of b₁, the estimated slope? (Round your answer to 3 decimal places, if needed.) Answer: (b) What is the value of b₀, the estimated intercept? (Round your answer to 3 decimal places, if needed.) Answer: (c) What is the percent of variation in the number of strikeouts that is explained by age, using linear regression? (Round your answer to 2 decimal places, if needed.) Answer: % (d) Can we use this linear regression to predict the number of strikeouts for a player age at 37?

Yes, because it is a linear relationship.

No, because the correlation coefficient is not 1.

No, because we cannot extrapolate.

No, because we are uncertain about the range of the number of strikeouts.

Yes, because we know the slope and intercept values.