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Interpret the Slope and the Y-Intercept of the Least-Squares Regression y^=β0+β1x\hat { y } = \beta _ { 0 } + \beta 1 \mathrm { x }

question 36

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Interpret the Slope and the y-intercept of the Least-Squares Regression Line
-Is there a relationship between the raises administrators at State University receive and their performance on the job? A faculty group wants to determine whether job rating (x) is a useful linear predictor of raise (y) . Consequently, the group considered the straight-line regression model, y^=β0+β1x\hat { y } = \beta _ { 0 } + \beta 1 \mathrm { x } . Using the method of least squares, the faculty group obtained the following prediction equation, y^=14,000+2,000x\hat { \mathrm { y } } = 14,000 + 2,000 \mathrm { x } . Interpret the estimated yy -intercept of the line.


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