Question

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. does the value of the y - intercept have meaning in this context? if so, interpret the y - intercept. if not, explain why. for every $1 million increase in salary, we predict the number of wins to increase by 60.7 wins, on average. the y - intercept does not have meaning in this context. it is not reasonable for a team to have a payroll of $0. we would predict the number of wins to be 60.7 if the payroll was zero. we would predict the number of wins to be 0.139 if the payroll was zero. for every $1 million increase in salary, we predict the number of wins to increase by 0.139 wins, on average.

Explanation:

In a regression context, the y - intercept is the predicted value of y when x = 0. Here, x is the payroll in millions of dollars. In the real - world scenario of Major League Baseball teams, it is not reasonable for a team to have a payroll of $0. So, the y - intercept has no practical meaning.

Answer:

The y intercept does not have meaning in this context. It is not reasonable for a team to have a payroll of $0.