Regression analysis between the selling price of a residential property (y in $1,000's) and the house size (x in 1,000's
Posted: Wed May 11, 2022 10:44 am
Regression analysis between the selling price of a residential
property (y in $1,000's) and the house size (x in 1,000's of square
feet) resulted in the following equation
y-hat = 150 + 140x
The correct interpretation of the slope (b1) is
A retail store's sales forecast is based on the number of
households nearby and store location. The estimated regression
equation is:
y-hat = 21.84 + 0.87(x1) - 6.86(x2) +
21.51(x3)
where: y = Weekly sales ($1000's)
x1 = Number of households (in 1000's) near
the store
x2 = 1 if store is located on a suburban
street
x3 = 1 if store is located in a shopping
mall
(x2 and x3 = 0 if store
located in city's downtown)
Referring to the regression equation above, the correct
interpretation of b0 is:
property (y in $1,000's) and the house size (x in 1,000's of square
feet) resulted in the following equation
y-hat = 150 + 140x
The correct interpretation of the slope (b1) is
A retail store's sales forecast is based on the number of
households nearby and store location. The estimated regression
equation is:
y-hat = 21.84 + 0.87(x1) - 6.86(x2) +
21.51(x3)
where: y = Weekly sales ($1000's)
x1 = Number of households (in 1000's) near
the store
x2 = 1 if store is located on a suburban
street
x3 = 1 if store is located in a shopping
mall
(x2 and x3 = 0 if store
located in city's downtown)
Referring to the regression equation above, the correct
interpretation of b0 is: