A realtor collects the data set given in DS 12.2.4 concerning the sizes of a random selection of newly constructed houses in a certain area together with their appraised values for tax purposes. 1. Fit a linear regression model with appraised value as the explanatory variable and size as the dependent variable.
2. What is the estimate of the error variance?

12.327X + 452.084

45206.327

Step-by-step explanation:

The linear regression model obtained by fitting the data using technology is :

ŷ = 12.327X + 452.084

Where, 12.327 = slope ; 452.084 = Intercept ; X = appraised value ; y = Area

The estimated error variance which is the degree of variation between the actual and predicted value.

Error variance = ΣSSE /n-2

n = sample size = 15

ΣSSE = 587682.2638

Error variance = 587682.2638/13

Error variance = 45206.327

6^2 or 36

step-by-step explanation:

6000n

6×1000n

6×10^3 n

so we need 6n need to be a perfect cube

so n has to be 6^2 so that 6n is 6^3

what i'm saying is if you let n be 6^2 you have 6^3×10^3 or 60^3 which is a perfect cube