Answer Happy

A. Using column (4), is the overall effect of size on price statistically significant? How would you go about testing this hypothesis? Match each question to the correct option What is the pull hypothesis for this test? Ho: At least one of B, and/or B2*0 What is the alternative hypothesis for this test? What is the appropriate test? CH: At least one of B, and/or B2 - 0 What is the appropriate critical value? Assume a 5% level of significance D. Ho B1=0 B. 2.30 E. F-test F. 164 G. Ho B1 + B2 = 0 H. 3.84 1 1.96 J. Ho: B1-B2 = 0 K. 3,00 L Hi: B, B20 M.H ₂: B 1 0 N t.test
Regressor (2) (3) (4) (5) Size (1) 0.00042 (0.000038) In(Size) 0.69 (0.054) 0.68 (0.087) 0.57 (2.03) 0.69 (0.055) In(Size) 0.0078 (0.14) Bedrooms 0.0036 (0.037) Pool 0.082 (0.032) 0.071 (0.034) 0.071 (0.035) 0.071 (0.034) 0.026 (0.026) 0.071 (0.036) 0.027 (0.029) View 0.037 (0.029) 0.027 (0.028) 0.027 (0.030) 0.0022 (0.10) Pool X View Condition 0.13 (0.045) 0.12 (0.036) 0.12 (0.035) 0.12 (0.035) 6,60 (0.39) 0.12 (0.035) 6.63 (0.53) Intercept 10.97 (0.069) 7.02 (7.50) 6.60 (0.40) Summary Statistics SER 0.102 0.098 0.099 0.099 0.099 R? 0.72 0.74 0.73 0.73 0.73 Variable definitions Price - sale price (5); Size - house size (in square foot); Bedrooms = number of bedrooms, Pool - binary variable (1 if house has a swimming pool, otherwise): View -- binary variable (1 if house has a nice view, otherwise); Condition binary variable (1 if real estate agent reports house is in excellent condition, otherwise).