# Use the data in Problem 4-22 and develop a regression model to predict selling price based on the square

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Use the data in Problem 4-22 and develop a regression model to predict selling price based on the square footage, number of bedrooms, and age. Use this to predict the selling price of a 10-year-old, 2,000-square-foot house with 3 bedrooms. also 1) State the linear equation.

2) Explain the overall statistical significance of the model.
3) Explain the statistical significance for each independent variable in the model
5) Is this a good predictive equation(s)? Which variables should be excluded (if any) and why? Explain.
SELLING SQUARE AGE
PRICE(\$) FOOTAGE BEDROOMS (YEARS)
64,000 1,670 2 30
59,000 1,339 2 25
61,500 1,712 3 30
79,000 1,840 3 40
87,500 2,300 3 18
92,500 2,234 3 30
95,000 2,311 3 19
113,000 2,377 3 7
115,000 2,736 4 10
138,000 2,500 3 1
142,500 2,500 4 3
144,000 2,479 3 3
145,000 2,400 3 1
147,500 3,124 4 0
144,000 2,500 3 2
155,500 4,062 4 10
165,000 2,854 3 3

• 7 years ago
Use the data in Problem 4-22 and develop a regression model to predict selling price based on the square
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• data.xlsx