A realtor is trying to predict the selling price of houses in Greenville (in thousands of dollars) as a function of Size (measured in thousands of square feet) and whether or not there is a replace (FF is 0 if there is no replace, 1 if there is a replace). Part of the regression output is provided below, based on a sample of 20 homes. Some of the information has been omitted. Variable Coefcients Standard Error t-Stat P-value Intercept 128.93746 2.6205302 49.203 8.93E-20 Size ??? 1.2072436 11.439 ??? FP 6.47601954 1.9803612 7?? 7?? Which of the following statement(s) is(are) supported by the regression output? i) Asmall house with a replace will always sell for less than a large house with no replace. ii) At a = 0.1, FF is a signicant predictor for predicting selling price. iii) Areplace adds around $6,476 to the selling price on average, when size is xed at constant level. And this added selling price is statistically signicant at 5% level. iv) For houses without replace. the average selling price increases slower with size than houses with replace. Note that lo.05 t0.025 df=191.729 2.093 df=181.734 2.101 df=171.740 2.110 O a. Only iii) O b.0nly ii) and iv) O C. Only ii) O d.Only ii) and iii) 0 e. Only i) O f. Only ii), iii), and iv) Q g. Only iv)