A regression was run to determine if for a certain baseball season, winning percentage, y, and on-base percentage, x, are linearly related. The results were: ˆ y =a+bx a=-0.4875 b=2.94 For this baseball season, the lowest on-base percentage was 0.310 and the highest was 0.362. (a) Write the equation of the Least Square Regression line. ˆ y = -0.4875 Correct + 2.94 x (b) Which is a possible value for the correlation coefficient, r? -1.143 1.235 0.72 -0.68 Correct (c) What does the slope mean in the context of this problem?

Calculus For The Life Sciences
2nd Edition
ISBN:9780321964038
Author:GREENWELL, Raymond N., RITCHEY, Nathan P., Lial, Margaret L.
Publisher:GREENWELL, Raymond N., RITCHEY, Nathan P., Lial, Margaret L.
Chapter2: Exponential, Logarithmic, And Trigonometric Functions
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A regression was run to determine if for a certain baseball season, winning percentage, y, and on-base percentage, x, are linearly related. The results were: ˆ y =a+bx a=-0.4875 b=2.94 For this baseball season, the lowest on-base percentage was 0.310 and the highest was 0.362. (a) Write the equation of the Least Square Regression line. ˆ y = -0.4875 Correct + 2.94 x (b) Which is a possible value for the correlation coefficient, r? -1.143 1.235 0.72 -0.68 Correct (c) What does the slope mean in the context of this problem? (d) As the on-base percentage increases by 5 percent, the predicted winning percentage increases Correct by 2.94 Incorrect percent. (e) Would it be a good idea to use this model to predict the winning percentage of a team whose on-base percentage is 0.156? Why or why not? (f) Based on this model, what would you expect the winning percentage to be for a team with on-base percentage 0.35? (Round your answer to three decimal places.)
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