Recall the real-estate dataset where we are interested to study the relationship between value and taxes by different locations 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 numerics factors in the dataset.

In the iteration one, the following model is obtained.

coefficients standard Error tstat P-Value Lower 95% Upper 95%

Intercept 2379.687211 585.367596 4.065287 0.000115 1214.071413 3545.30301

Value 11.15718872 2.008324021 5.555472 3.81E-07 7.158104689 15.15627276

LotSize -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 insignificant variable, and the result is shown below

coefficients Standard Error tstat P-Value Lower %95 Upper 95%

Intercept 2491.14276 551.71834 4.515244 2.18E-05 1392.974874 3589.310646

Value 10.88546691 1.87747437 5.797931 1.32E-07 7.148447659 14.62248617

Bathrooms 669.7126817 168.2187561 3.981201 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 the 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 the regression analysis? value=356, lotsize=18, bedroom=4,bathroom=3, rooms=10, age=5.