Question

Data were collected from a random sample of 340 home sales from a community in 2003. Let Price denote the selling price​ (in $1,000), BDR denote the number of​ bedrooms, Bath denote the number of​ bathrooms, Hsize denote the size of the house​ (in square​ feet), Lsize denote the lot size​ (in square​ feet), Age denote the age of the house​ (in years), and Poor denote a binary variable that is equal to 1 if the condition of the house is reported as​ "poor."

An estimated regression​ yields:

Price = 113.2 + 0.461BDR + 22.2Bath + 0.148Hsize + .002Lsize

(22.7) (2.79) (8.49) (.010) (.00046)

+.086Age - 46.4Poor, R^2 = .68, SER = 39.4

(.295) (10.0)

1. The 99​% confidence interval for the effect of lot size on price is (___,___)? (Round to two decimal places.)

2. The degree of freedom to test if the coefficients on BDR and Age are statistically different from zero at the 10​% level is?

Answer 1

1)

The 99​% confidence interval for the effect of lot size on price

df = n-k = 340-7 = 333, alpha = 0.01

tc = 2.5907

CI = b4 +/ tc*Sb4

Here b4 = 0.002, Sb4 = 0.00046

CI = 0.002 +/- 2.5907*0.00046

CI = (0.0008, 0.0032)

CI = (0.00, 0.00)

2)

The degrees fredom = n-k = 340-7 = 333

BDR:

t test = b1/Sb1 = 0.461/2.79 = 0.1652

P value = 0.8689 > 0.1, Do not Staristically Significant

Age:

t test = b5/Sb5 = 0.086/0.295 = 0.2915

P value = 0.7708 > 0.1, Do not Staristically Significant