Given the following apartments pricing dataset, apply multiple linear regression to predict apartment price given the number of rooms and the floor of the apartment. What is the rule that will be used to estimate the regression parameters BETAs? a. BETAs equals y(inv(XX))X b. None of them c. BETAs equals (inv( (XX))Xy d. BETAs equals ( XX)Xy Transposed features matrix will be of size a. 6 columns and 2 rows b. 6 columns and 3 rows c. 3 columns and 6 rows d. 2 columns and 6 rows Regression parameters vector that include Bias, weight for NRooms, and weight for Floor is as follows a. 116.4,108.2, and 0.7 b. 9.1,137.9, and 55.9 c. 314.8,154.1, and 7.9 d. 128.8,164.4, and 36.3 e. 110.7,6.4, and 87.1 Which cofounding variable is the most affecting the price? a. Number of rooms b. Floor c. Bias d. None of them What is the price of an apartment that has four rooms and located in the third floor according to your model? a. 809 b. 785 c. 955 d. 994 e. 1010