Question

shows? 3. Using data on the appraised value of homes, a real estate agent computes the least- squares regression line for predicting a home's value in 2002 from its value in 1992. The equation of the least-squares regression line is: where y represents a home's value in 2002 and x is the value in 1992. $44,000+1.8x y Question: Explain y, $22,000, 1.6 and x separately? Suppose Julia owns a home that was worth $100,000 in 1992. What would be the predicted value of his home in 2002? a) b)
need answer asap please

Answer 1

Least Square regression line is:

y = $44,000 + 1.8x

a). y = Predicted value of homes in 2002

      x = Actual value of homes in 1992

     $44,000 = Intercept of the regression equation

     1.8 = Slope of the regression equation. If we increase 1 unit in the value of x then the value of y would be increased by 1.8

Note: Here we have $22,000 and 1.6 which are different value from the above although.

b). Julia owns a home that was worth $100,000 in 1992; The predicted value of his home in 2002 would be

= $44,000 + (1.8 * $100,000)

                 = $44,000 + $180,000

                 = $224,000

PLEASE LET ME KNOW IF YOU HAVE ANY DOUBTS. THANKS!!