A sports statistician was interested in the relationship between game attendance (in thousands) and the number of wins for baseball teams. Information was collected on several teams and was used to obtain the regression equation ŷ = 4.9x + 15.2, where x represents the attendance (in thousands) and ŷ is the predicted number of wins. Which statement best describes the meaning of the y-intercept of the regression line? When the number of wins is 0, the predicted attendance is 0. When the number of wins is 0, the predicted attendance is 15,200. When the attendance is 0, the predicted number of wins is 4.9 When the attendance is 0, the predicted number of wins is 15.2.

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A sports statistician was interested in the relationship between game attendance (in thousands) and the number of wins for baseball teams. Information was collected on several teams and was used to obtain the regression equation  = 4.9x + 15.2, where x represents the attendance (in thousands) and  is the predicted number of wins. Which statement best describes the meaning of the y-intercept of the regression line?

When the number of wins is 0, the predicted attendance is 0.
When the number of wins is 0, the predicted attendance is 15,200.
When the attendance is 0, the predicted number of wins is 4.9
When the attendance is 0, the predicted number of wins is 15.2.
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