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(b) Develop an estimated regression equation that can be used to predict the selling price given the three independent variables (number of baths, square footage, and number of bedrooms). (Round your numerical values to two decimal places. Let x₁ represent the number of baths, x₂ represent the square footage, x3 represent the number of bedrooms, and y represent the selling price.) ŷ = X Check if you have any variable(s)/term(s) missing from your equation. (c) It is argued that we do not need both number of baths and number of bedrooms. Develop an estimated regression equation that can be used to predict selling price given square footage and the number of bedrooms. (Round your numerical values to two decimal places. Let x₁ represent the square footage, x, represent the number of bedrooms, and y represent the selling price.) ŷ = (d) Suppose your house has four bedrooms and is 2,850 square feet. What is the predicted selling price (in $) using the model developed in part (c). (Round your answer to the nearest cent.) $ ×

(b) Develop an estimated regression equation that can be used to predict the selling price given the three independent variables (number of baths, square footage, and number of bedrooms). (Round your numerical values to two decimal places. Let x₁ represent the number of baths, x₂ represent the square footage, x3 represent the number of bedrooms, and y represent the selling price.) ŷ = X Check if you have any variable(s)/term(s) missing from your equation. (c) It is argued that we do not need both number of baths and number of bedrooms. Develop an estimated regression equation that can be used to predict selling price given square footage and the number of bedrooms. (Round your numerical values to two decimal places. Let x₁ represent the square footage, x, represent the number of bedrooms, and y represent the selling price.) ŷ = (d) Suppose your house has four bedrooms and is 2,850 square feet. What is the predicted selling price (in $) using the model developed in part (c). (Round your answer to the nearest cent.) $ ×

Glencoe Algebra 1, Student Edition, 9780079039897, 0079039898, 2018
Glencoe Algebra 1, Student Edition, 9780079039897, 0079039898, 2018
18th Edition
ISBN:9780079039897
Author:Carter
Publisher:Carter
Chapter4: Equations Of Linear Functions
Section4.5: Correlation And Causation
Problem 22PFA
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Spring is a peak time for selling houses. The table below contains the selling price, number of bathrooms, square footage, and number of bedrooms of 26 homes in a certain city. Selling Price 160,000 170,000 178,000 182,500 195,100 212,500 245,900 250,000 255,000 258,000 267,000 268,000 275,000 Baths Sq Ft Beds 1.5 1,786 2 1,768 1 1,219 1 1,578 1.5 1,125 2 1,196 2 2,128 3 1,280 2 1,596 3.5 2,374 2.5 2,439 2 1,470 2 1,668 3 3 3 2 4 2 3 3 3 4 3 4 4 Selling Price 295,000 325,000 325,000 328,400 331,000 344,500 365,000 385,000 395,000 399,000 430,000 430,000 454,000 Baths Sq Ft Beds 2.5 1,860 2 2,056 3.5 2,776 2 1,408 1,972 1.5 2.5 1,736 2.5 1,990 2.5 3,640 2.5 1,908 2 2 2,462 2 2,108 3.5 2,615 3,700 3 4 4 3 3 3 4 4 4 3 4 4 4
Transcribed Image Text:Spring is a peak time for selling houses. The table below contains the selling price, number of bathrooms, square footage, and number of bedrooms of 26 homes in a certain city. Selling Price 160,000 170,000 178,000 182,500 195,100 212,500 245,900 250,000 255,000 258,000 267,000 268,000 275,000 Baths Sq Ft Beds 1.5 1,786 2 1,768 1 1,219 1 1,578 1.5 1,125 2 1,196 2 2,128 3 1,280 2 1,596 3.5 2,374 2.5 2,439 2 1,470 2 1,668 3 3 3 2 4 2 3 3 3 4 3 4 4 Selling Price 295,000 325,000 325,000 328,400 331,000 344,500 365,000 385,000 395,000 399,000 430,000 430,000 454,000 Baths Sq Ft Beds 2.5 1,860 2 2,056 3.5 2,776 2 1,408 1,972 1.5 2.5 1,736 2.5 1,990 2.5 3,640 2.5 1,908 2 2 2,462 2 2,108 3.5 2,615 3,700 3 4 4 3 3 3 4 4 4 3 4 4 4
(b) Develop an estimated regression equation that can be used to predict the selling price given the three independent variables (number of baths, square footage, and number of bedrooms). (Round your numerical values to two decimal places. Let x₁ represent the number of baths, x₂ represent the square footage, x3 represent the number of bedrooms, and y represent the selling price.) ŷ = X Check if you have any variable(s)/term(s) missing from your equation. (c) It is argued that we do not need both number of baths and number of bedrooms. Develop an estimated regression equation that can be used to predict selling price given square footage and the number of bedrooms. (Round your numerical values to two decimal places. Let X₁ represent the square footage, x₂ represent the number of bedrooms, and y represent the selling price.) ŷ = (d) Suppose your house has four bedrooms and is 2,850 square feet. What is the predicted selling price (in $) using the model developed in part (c). (Round your answer to the nearest cent.) $
Transcribed Image Text:(b) Develop an estimated regression equation that can be used to predict the selling price given the three independent variables (number of baths, square footage, and number of bedrooms). (Round your numerical values to two decimal places. Let x₁ represent the number of baths, x₂ represent the square footage, x3 represent the number of bedrooms, and y represent the selling price.) ŷ = X Check if you have any variable(s)/term(s) missing from your equation. (c) It is argued that we do not need both number of baths and number of bedrooms. Develop an estimated regression equation that can be used to predict selling price given square footage and the number of bedrooms. (Round your numerical values to two decimal places. Let X₁ represent the square footage, x₂ represent the number of bedrooms, and y represent the selling price.) ŷ = (d) Suppose your house has four bedrooms and is 2,850 square feet. What is the predicted selling price (in $) using the model developed in part (c). (Round your answer to the nearest cent.) $
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