Split the dataset into a “training dataset” and a “validation set”. Ensure that the training dataset is 80% of the data and the validation is 20%.

1. Estimate a multiple regression by adding “Lotsize” and “Bath” as explanatory variables. Interpret all estimated coefficients.

b. What is the RMSE of the model in the training dataset? What is the RMSE of the model on the validation dataset? 

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Obs 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 62272282 18 19 20 21 23 24 25 29 30 Price SqFt LotSize 505.5 2192 16.4 784.1 3429 24.7 649.0 2842 17.7 689.8 2987 20.3 709.8 3029 22.2 590.2 2616 20.8 643.3 2978 17.3 789.7 3595 22.4 683.0 2838 27.4 544.3 2591 19.2 822.8 3633 26.9 637.7 2822 23.1 618.7 2994 20.4 619.3 2696 22.7 490.5 2134 13.4 675.1 3076 19.8 710.4 3259 20.8 674.7 3162 19.4 663.6 2885 23.2 606.6 2550 20.2 758.9 3380 19.6 723.7 3131 22.5 621.8 2754 19.2 622.4 2710 21.6 631.3 2616 20.8 574.0 2608 17.3 863.8 3572 29.0 21.8 844.2 3614 25.5 629.9 2600 24.1 652.7 2924 Baths 2.5 3.5 3.5 3.5 3.0 2.5 3.0 3.5 3.0 2.0 4.0 3.0 3.0 3.5 2.5 3.0 3.5 4.0 3.0 3.0 4.5 3.5 2.5 3.0 2.5 3.5 4.0 2.5 3.5 3.5 Obs 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 62272282 18 19 20 21 23 24 25 29 30 Price SqFt LotSize 505.5 2192 16.4 784.1 3429 24.7 649.0 2842 17.7 689.8 2987 20.3 709.8 3029 22.2 590.2 2616 20.8 643.3 2978 17.3 789.7 3595 22.4 683.0 2838 27.4 544.3 2591 19.2 822.8 3633 26.9 637.7 2822 23.1 618.7 2994 20.4 619.3 2696 22.7 490.5 2134 13.4 675.1 3076 19.8 710.4 3259 20.8 674.7 3162 19.4 663.6 2885 23.2 606.6 2550 20.2 758.9 3380 19.6 723.7 3131 22.5 621.8 2754 19.2 622.4 2710 21.6 631.3 2616 20.8 574.0 2608 17.3 863.8 3572 29.0 21.8 844.2 3614 25.5 629.9 2600 24.1 652.7 2924 Baths 2.5 3.5 3.5 3.5 3.0 2.5 3.0 3.5 3.0 2.0 4.0 3.0 3.0 3.5 2.5 3.0 3.5 4.0 3.0 3.0 4.5 3.5 2.5 3.0 2.5 3.5 4.0 2.5 3.5 3.5