The 12 data samples and their corresponding predicted probability values are shown in the table below. No. size price status predicted prob. 5.20 1.15 0.985 5.40 1.40 0.935 6.00 1.35 0.902 6.20 1.06 0.970 6.30 1.95 HOOOHOOOO 0.227 6.65 0.70 0.992 7.00 1.27 0.810 7.20 1.00 0.931 8.80 1.80 0.033 9.20 1.45 0.113 10.00 0.60 0.798 12 11.00 0.80 0.3042. (12 points) A logistic regression model has been obtained to predict if a at will be sold Within 3 months it is advertised on a new online property portal. The relevant data features are as follows: 0 Target feature: status (= 0 if the property was not sold within 3 months, = 1 if the property was sold within 3 months). 0 Descriptive feature 1: size (in hundreds of square feet) 0 Descriptive feature 2: selling price per square foot (in thousands of dollars) The relevant parameters in the logistic regression model built to predict. (status = 0) are: Parameter Estimate Std. Error Wald Chi-Square Pr > ChiSq Intercept 16.2106 8.2485 3.8623 0.0494 size -1.1750 0.6560 3.2086 0.0733 price -5.1438 2.9371 3.0671 0.0799