A real estate magazine reported the results of a regression analysis designed to predict the price (y), measured in dollars, of residential properties recently sold in a northern Virginia subdivision. One independent variable used to predict sale price is GLA, gross living area (x), measured in square feet. Data for 157 properties were used to fit the model, = [Math Processing Error]

The results of the simple linear regression are provided below. = [Math Processing Error]
Interpret the estimate of [Math Processing Error], the y-intercept of the line.

let take the method  ^y = 22.5x +96,600  

Step-by-step explanation:

All residential properties in Virginia will sell for at least $96,600.

For each 1-sq ft rise in GLA, a property's sale price is expected  to go above $96,600.

Sale prices as observed would fall within$96,600 of the least squares line., as about 95% is discovered.

 There is no value given, since a gross area of zero a not a constant value

then, the surface area of the sphere shown in the image is: 256π sq. units!

step-by-step explanation:

the lateral surface area of a sphere is 2πrh where h=2r.

then:

surface area = 4πr^2.

in this case, r=8 units ⇒ surface area = 4π(8 units)^2. = 256π sq. units!

then, the surface area of the sphere shown in the image is: 256π sq. units!

jwjwkwkwkkkdjebd b jdjejdndj he jenej