A regression analysis was done of residential property values in a portion of a city. The dependent variable is Sale Price (Y) and the independent variable is Square Footage (X). Data for 157 properties were used in the regression. The results are listed below.
Predicted Y = 96,600 + 22.5(X) R-square = .77
What is the predicted value of Sale Price if the property has 2500 square feet?

A. $56,250.00
B. $152,850.00
C. $96,622.50
D. $96,600.00

So then the correct option for this case would be:

B. $152,850.00

Step-by-step explanation:

They adjust a linear model using the least squares method

For this case we assume that they calculate the slope with the following formula:

Where:

And we can find the intercept using this:

After apply the method they obtain the following regression equation:

Where Y represent the sale price and X the square footage.

And we want to estimate the predicted value of Sale price if the property has a 2500 square footage.

So for this case we just need to replace into our original equation the value of X = 2500 and we got:

So then the correct option for this case would be:

B. $152,850.00

answer: 12

step-by-step explanation:

because yes

(b) 240

step-by-step explanation:

first, we use the pythagorean formula using the given side lengths to find x. then we use x to find the side lengths. then we add the side lengths to find the perimeter.

pythagorean theorem formula:

a^2 + b^2 = c^2

(x - 20)^2 + (x - 40)^2 = x^2

x^2 - 40x + 400 + x^2 - 80x + 1600 = x^2

x^2 -120x + 2000 = 0

(x - 100)(x - 20) = 0

x - 100 = 0 or x - 20 = 0

x = 100 or x = 20

we see that the solution x = 20 must be discarded because it will give a negative side length and a side length of 0. the only valid solution is x = 100.

perimeter = sum of the lengths of the sides

perimeter = x + x - 20 + x - 40

perimeter = 3x - 60

replace x with 100.

perimeter = 3(100) - 60

perimeter = 300 - 60

perimeter = 240