Recall the real-estate dataset where we are interested to study the relationship between value and taxes by different location. It was decided that a closer look at location D is needed by developing a linear regression model to explain how taxes are calculated based on values and other numeric factors in the dataset. In the iteration one, the following model is obtained. Standard Coefficients t Stat P-value Lower 95% Upper 95% Error Intercept Value LotSize 2379.687211 585.367596 4.065287 0.000115 1214.071413 3545.30301 11.15718872 2.008324021 5.555472 3.81-07 7.158104689 15.15627276 -0.471685292 14.82343802 -0.03182 0.974698 -29.98892141 29.04555083 Bedrooms 97.13652008 136.2196847 0.713087 0.477947 -174.1115258 368.384566 Bathrooms 648.3186488 172.5325558 3.75766 0.000332 304.7624387 991.8748588 Rooms 182.8486399 89.16002462 2.050792 0.04369 5.308348989 360.3889308 Age -17.75957249 4.65134013 -3.81816 0.00027 -27.02157397 -8.497571015

A second iteration was done by removing insi gnificant variable, and the result is shown below P-value Lower 95% Upper 95% 4.515244 2.18E-05 1392.974874 3589.310646

Coefficients Standard Error t Stat

Intercept 2491.14276 551.71834

Value

10.88546691 1.87747437 5.797931 1.32E-07 7.148447659 14.62248617

Bathrooms 669.7126817 168.21875613.981201 0.000151 334.8816234 1004.54374

Rooms

224.1874185 66.00725664 3.396406 0.001071 92.80326065 355.5715764 Age

-18.49817831 4.443169268-4.16328 7.94-05 -27.34208551 -9.654271108 a. for the 6 numeric variables, which of them are considered NOT predictive for taxes based on th regression analysis? b. explain the meaning of the slope of the predictive variables. c. what should be the taxes amount for the following new property in location D according to t regression analysis? value=356, lotsize=18, bedroom=4,bathroom=3, rooms=10, age=5.