A multiple linear regression analysis was carried out using the following data for 60 residential housing sales in a given area in the east coast of the USA in 2019: Y = Sales Price (in thousands of dollars). X1 = Living Area (in square feet) X2 = 1 if the house is on the waterfront = 0 if the house is not on the waterfront X3 = 1 if the house has a garage = 0 if the house does not have a garage The results of a regression analysis used to predict housing sales are as follows: \\ U 1. Prediction equation: Y = -28 + 0.088X1 + 280X2 + 35x3 2. The F test is statistically signicant. 3. The three T tests are statistically signicant. 4. The value of SSE = 35,000. 5. The value of SSR = 315,000. 6. The residual plots exhibited a random pattern with no outliers present. Two houses have the same number of square feet of living area. The rst house is a waterfront house without a garage. The second house is a nonwaterfront house with a garage. Estimate the difference in the sales prices of these two houses. 0 $230,000 0 $245,000 0 $315,000 0 $35,000 0 $350,000