Respuesta :
Answer:
[tex] Y= 96600+ 22.5*2500= 152850[/tex]
So then the correct option for this case would be:
B. $152,850.00
Step-by-step explanation:
They adjust a linear model [tex] y = mx +b[/tex] using the least squares method
For this case we assume that they calculate the slope with the following formula:
[tex]m=\frac{S_{xy}}{S_{xx}}[/tex]
Where:
[tex]S_{xy}=\sum_{i=1}^n x_i y_i -\frac{(\sum_{i=1}^n x_i)(\sum_{i=1}^n y_i)}{n}[/tex]
[tex]S_{xx}=\sum_{i=1}^n x^2_i -\frac{(\sum_{i=1}^n x_i)^2}{n}[/tex]
[tex] \bar X =\frac{\sum X}{n}[/tex]
[tex] \bar Y =\frac{\sum Y}{n}[/tex]
And we can find the intercept using this:
[tex]b=\bar y -m \bar x[/tex]
After apply the method they obtain the following regression equation:
[tex] Y = 96600 + 22.5 X[/tex]
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:
[tex] Y= 96600+ 22.5*2500= 152850[/tex]
So then the correct option for this case would be:
B. $152,850.00
