You are interested in examining the determinants of housing prices. You get the following estimated regression results: price Coef. Std. Err. crime - 66. 34801 35.94711 rooms 5409 . 401 441 . 6634 proptax -56 . 43813 19 . 2566 lowstat -499 . 5402 49 . 18814 _cons -2592.909 3195 . 554 Where price is in dollars, rooms are the number of bedrooms, proptax is the property tax per 1000, lowstat is the percentage of people of supposedly "lower" status. The sum of squared residuals for this model is 15219 and the sum of squared totals is 42826. There are 506 total observations in the data. Answer the following questions. Round to 2 decimal places and include a negative sign if necessary. A. Is crime a statistically significant determinant of housing prices at the 95% confidence level? Answer "YES" or "NO" B. Is the number of bedrooms a statistically significant determinant of housing prices at the 95% confidence level? Answer "YES" or "NO" C. Is the amount of property tax charged a statistically significant determinant of housing prices at the 95% level? Answer "YES" or "NO" D. Is the amount of "low status" people nearby a statistically significant determinant of housing prices at the 95% level? Answer "YES" or "NO" E. Calculate R" . Be careful, this is rbar. Round to 2 decimal places. Keep your answer in decimal form, NOT percentage form. F. Suppose that you forgot to include the variable, Zoning, which measures the degree of restrictive zoning rules imposed in that area. You also know the following characteristics: corr(Zoning, Price) > 0 corr(Zoning, LowStat)