earlier we investigated the relationship between x = payroll (in millions of dollars) and y = number of wins…

earlier we investigated the relationship between x = payroll (in millions of dollars) and y = number of wins for major league baseball teams in 2016. given is a scatterplot of the data, along with the regression line ŷ = 60.7 + 0.139x. interpret the slope of the regression line. the slope is 60.7. the predicted number of wins goes up by 60.7 for each increase of $1 million in payroll. the slope is 0.139. the predicted number of wins goes up by 0.139 for each increase of $1 million in payroll. the slope is 0.139. the predicted number of wins goes down by 0.139 for each increase of $1 million in payroll. the slope is 60.7. the predicted amount of payroll goes down by $60.7 for each increase of 1 game won. the slope is 60.7. the predicted number of wins goes down by 60.7 for each increase of $1 million in payroll.

earlier we investigated the relationship between x = payroll (in millions of dollars) and y = number of wins for major league baseball teams in 2016. given is a scatterplot of the data, along with the regression line ŷ = 60.7 + 0.139x. interpret the slope of the regression line. the slope is 60.7. the predicted number of wins goes up by 60.7 for each increase of $1 million in payroll. the slope is 0.139. the predicted number of wins goes up by 0.139 for each increase of $1 million in payroll. the slope is 0.139. the predicted number of wins goes down by 0.139 for each increase of $1 million in payroll. the slope is 60.7. the predicted amount of payroll goes down by $60.7 for each increase of 1 game won. the slope is 60.7. the predicted number of wins goes down by 60.7 for each increase of $1 million in payroll.

Answer

Explanation:

Step1: Recall slope - intercept form

The regression line is in the form $\hat{y}=a + bx$, where $b$ is the slope. Here, $\hat{y}=60.7 + 0.139x$, so the slope $b = 0.139$.

Step2: Interpret the slope

The slope represents the change in the response variable ($\hat{y}$, number of wins) for a one - unit change in the explanatory variable ($x$, payroll in millions of dollars). For each increase of 1 million dollars in payroll ($x$ increases by 1), the predicted number of wins ($\hat{y}$) goes up by 0.139.

Answer:

The slope is 0.139. The predicted number of wins goes up by 0.139 for each increase of $1 million in payroll.