2. Considering all of the models shown in the table above, which regression equation is best for predicting sale price? Explain your answer. 3. Using the model you selected in question 2, predict the sale prices for ONE of the following houses listed by this agent last month: Smith House: 16 years old, 2000 square feet, list price is $640,000 Gomez House: 3 years old, 2450 square feet, list price is $855,000 Singh House: 8 years old, 1475 square feet, list price is $575,000 NOTE: If your model includes the list price, you must change the list price to $1000s to use in the regression equation: Smith is 640, Gomez 855, Singh 575 4. Suppose the house you selected in question 3 was sold for the price shown here: Smith House: $595,000 Gomez House: $790,000 Singh House: $550,000 Calculate the residual for your prediction. Remember to convert the sale prices to $1000s, before calculating the residual. 5. For the house you selected, did the regression model you used predict a better outcome for the seller or the buyer? Explain your answer using information from your previous answers.A real estate agent is interested in building a regression model to predict the selling price of a home. She hopes this model will assist with determining appropriate list prices. The agent collected the following variables from 100 homes recently sold in her town: Age (in years), Square feet, List Price (in $1000 units) and Sale Price (in $1000 units) The agent has hired you to select the best regression model to predict the sale price (SP) using one or more of the predictor variables, Age (AGE), Square feet (SQFT), List Price (LP). The table below lists seven (7) possible regression models that you have calculated. Adused A Regression Equation 25.275.43 0581 0.573 P-1 1305-21.973 1(age) Square feet 0.271 F- 31.665+02601(spare leed) List Price 1 81 1.6 1970 0.970 "= 12.029 + 0.8713(list price) 10.434.21 1.823 P= 356.55-9.25hage)+0.197(square fecth Aga Lit price "- 42498-0.775[age) +0.859(list price) Square feet, List price 1,764.10 0.573 0.970 - 2869+0.0303(square feet) + 1.524(list price) Age, Square feet, List 1, 762.71 0.971 0.970 "=34.104-0.797(ace) +0 0203(square feet)+0.805(list price) Price Initial Posting: Use the information in table below to answer the following questions. 1. If the agent wants a regression model with one predictor variable, which model is best? Why did you pick this model