Using a linear-regression equation to predict values outside the range of the data is an example of a) extrapolation b) interpolation c) least-squares fit d) residuals

An engineer wants to determine how the weight of a​ gas-powered car,​ x, affects gas​ mileage, y. The accompanying data represent the weights of various domestic cars and their miles per gallon in the city for the most recent model year. Complete parts​ (a) through​ (d) below. LOADING... Click here to view the weight and gas mileage data.       Question content area bottom Part 1 ​(a) Find the​ least-squares regression line treating weight as the explanatory variable and miles per gallon as the response variable.   ModifyingAbove y with caretyequals=negative 0.00756−0.00756xplus+​(44.844.8​) ​(Round the x coefficient to five decimal places as needed. Round the constant to one decimal place as​ needed.) Part 2 ​(b) Interpret the slope and​ y-intercept, if appropriate. Choose the correct answer below and fill in any answer boxes in your choice. ​(Use the answer from part a to find this​ answer.)   A. For every pound added to the weight of the​ car, gas mileage in the…

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An engineer wants to determine how the weight of a​ gas-powered car,​ x, affects gas​ mileage, y. The accompanying data represent the weights of various domestic cars and their miles per gallon in the city for the most recent model year. Complete parts​ (a) through​ (d) below. LOADING... Click here to view the weight and gas mileage data.       Question content area bottom Part 1 ​(a) Find the​ least-squares regression line treating weight as the explanatory variable and miles per gallon as the response variable.   ModifyingAbove y with caretyequals=enter your response herexplus+​(enter your response here​) ​(Round the x coefficient to five decimal places as needed. Round the constant to one decimal place as​ needed.)