Final answer:
a. Size is the independent variable, and price is the dependent variable. b. The independent variable is Size, and the dependent variable is Price. c. The intercept does not have a practical interpretation. d. The slope represents the change in price for every additional unit increase in house size. e. The predicted price for a house size of 2,000 square feet is $185.791.
Step-by-step explanation:
The questions can be answered as -
a. Size is the independent variable, and price is the dependent variable.
b. The independent variable is Size, and the dependent variable is Price.
c. The intercept in the linear model, -3.117, represents the estimated price when the size of the house is 0. However, since a house with a size of 0 is not meaningful in this context, the intercept does not have a practical interpretation.
d. The slope in the linear model, 94.454, represents the change in price (in thousands of dollars) for every additional unit increase in house size (in thousands of square feet). So, for every 1,000 square feet increase in size, the predicted price increases by $94,454.
e. To find the predicted price for a house size of 2,000 square feet, we can substitute the size value into the regression equation: Price = -3.117 + 94.454 * Size. Therefore, the predicted price for a house size of 2,000 square feet is -3.117 + 94.454 * 2 = $185.791 (in thousands of dollars).