Price | SqFt | Brick | Salary | Experience | Service | Industrial |
241255 | 3392 | 0 | 133125 | 6 | 0 | 1 |
184518 | 2038 | 1 | 126200 | 2 | 1 | 0 |
176488 | 1906 | 0 | 195729 | 23 | 0 | 0 |
240068 | 3329 | 0 | 217435 | 28 | 0 | 0 |
169760 | 1828 | 0 | 147113 | 13 | 0 | 1 |
185335 | 2081 | 0 | 158000 | 21 | 0 | 1 |
172735 | 1926 | 0 | 148363 | 15 | 1 | 0 |
224281 | 3425 | 0 | 160165 | 12 | 0 | 0 |
172589 | 1676 | 1 | 132750 | 1 | 0 | 1 |
214635 | 2735 | 1 | 160500 | 23 | 0 | 1 |
199666 | 2373 | 1 | 183625 | 21 | 0 | 0 |
208348 | 2662 | 1 | 166975 | 30 | 1 | 0 |
218360 | 2834 | 1 | 144400 | 12 | 1 | 0 |
230160 | 3254 | 0 | 159913 | 29 | 1 | 0 |
164812 | 1431 | 0 | 190813 | 21 | 0 | 0 |
191560 | 1839 | 1 | ||||
203255 | 2456 | 1 | ||||
173325 | 1530 | 0 | ||||
168073 | 1381 | 1 | ||||
179620 | 1457 | 1 |
35)
The predicted value of the house price when SqFt is 2275 and it is made of brick is
Price = 111974 + 35.619*2275 + 5683 *1 = $ 198689.
Q 31) The p-value for the test of slope corresponding to the independent variable SqFt is 0.000 and less than 0.01. Hence, we can conclude that the coefficient of SqFt is significant at the 0.01 level of significance.
Ans: Yes.
Q. 39.
The expected salary for a CEO who is the service sector with 14 years of experience is
Salary = 155889 - 34933*1+ 1603.1*14 - 30111*0=143400
Ans: $ 143400
please help thank you! Selling Information For Real Estate Value Price SqFt Brick (1 if brick,...
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The table below yves the list price and the number of bids received for five randomly selected items sold through online auctions. Using this data, consider the equation of the regression line. ☺ = be+bx, for predicting the number of bids an item will receive based on the list price. Keep in mind, the correlation coefficient may or may not be statistically significant for the data given. Remember, in practice, it would not be appropriate to use the regression line...
The table below gives the list price and the number of bids received for five randomly selected items sold through online auctions. Using this data, consider the equation of the regression line, yˆ=b0+b1xy^=b0+b1x, for predicting the number of bids an item will receive based on the list price. Keep in mind, the correlation coefficient may or may not be statistically significant for the data given. Remember, in practice, it would not be appropriate to use the regression line to make...