Question

In: Statistics and Probability

2) The following data gives the selling price, square footage, number of bedrooms, and the age...

2) The following data gives the selling price, square footage, number of bedrooms, and the age of a house in years. These houses have been sold in a specific neighborhood over the last six months.

Selling Price ($)

Square Footage

Bedrooms

Age (years)

84,000

1,670

2

30

79,000

1,339

2

25

91,500

1,712

3

30

120,000

1,840

3

40

127,500

2,300

3

18

132,500

2,234

3

30

145,000

2,311

3

19

164,000

2,377

3

7

155,000

2,736

4

10

168,000

2,500

3

1

172,500

2,500

4

3

174,500

2,479

3

3

175,000

2,400

3

1

177,500

3,124

4

0

184,000

2,500

3

2

195,500

4,062

4

10

195,000

2,854

3

3

a) Using square footage develop a model to predict the selling price of the house. How well does the model fit the data? What percentage of the selling price is explained by the model?

b) Using the number of bedrooms develop a model to predict the selling price of the house. How well does the model fit the data? What percentage of the selling price is explained by the model?

c) Using the age of the house develop a model to predict the selling price of the house. How well does the model fit the data? What percentage of the selling price is explained by the model?

d) Which of the models estimated in parts a – d best fits the data? Why did you select that model?

Solutions

Expert Solution

Q.a) ans

X=square footage

Y= selling price

correlation coefficient is 0.8363

The percentage of the selling price is explained by the model is (correlation coefficient)^2 = (0.8363)^2 = 0.6994

69.9% of selling price is explained by model

Q.b) ans

Here X : number bedrooms

Y: selling price

Correlation coefficient = 0.6577

The percentage of selling price explained by the model is given by (0.6577)^2 = 0.4325 = 43.2%

Q.c) ans

X : age of the house

Y : selling Price

Correlation coefficient = -.8385

The percentage of selling price explained by the model is given by (-0.8385)^2 = 0.70308 = 70%

Q.d) ans

As we known higher the value of coefficient indicator of goodness of fit.

70.3% variation in selling price explained by model in part c i.e. regression model of age of the house & selling price

Most of the points in part in regression line plot are lies on regression line..so it indicates goodness of fit.

Model in part c (regression model of age of house & selling price) is best model.


Related Solutions

2) The following data gives the selling price, square footage, number of bedrooms, and the age...
2) The following data gives the selling price, square footage, number of bedrooms, and the age of a house in years. These houses have been sold in a specific neighborhood over the last six months. Selling Price ($) Square Footage Bedrooms Age (years) 84,000 1,670 2 30 79,000 1,339 2 25 91,500 1,712 3 30 120,000 1,840 3 40 127,500 2,300 3 18 132,500 2,234 3 30 145,000 2,311 3 19 164,000 2,377 3 7 155,000 2,736 4 10 168,000...
The following data gives the selling price, square footage, number of bedrooms, and the age of...
The following data gives the selling price, square footage, number of bedrooms, and the age of a house in years. These houses have been sold in a specific neighborhood over the last six months. Selling Price ($) Square Footage Bedrooms Age (years) 84,000 1,670 2 30 79,000 1,339 2 25 91,500 1,712 3 30 120,000 1,840 3 40 127,500 2,300 3 18 132,500 2,234 3 30 145,000 2,311 3 19 164,000 2,377 3 7 155,000 2,736 4 10 168,000 2,500...
The following data gives the selling price, square footage, number of bedrooms, and age (in years)...
The following data gives the selling price, square footage, number of bedrooms, and age (in years) of condominiums that were sold in a neighborhood in the Bronx in the past six months             Selling Price Square Footage No. of Bedrooms Age of Condo 64000 1670 2 30 59000 1339 2 25 61500 1712 3 30 79000 1840 3 40 87500 2300 3 18 92500 2234 3 30 95000 2311 3 19 113000 2377 3 7 115000 2736 4 10 138000...
The following data give the selling price, square footage, number of bedrooms, and age of houses...
The following data give the selling price, square footage, number of bedrooms, and age of houses that have sold in a neighborhood in the past 6 months. Develop three regression models to predict the selling price based upon each of the other factors individually. Which of these is best? use 1 for yes and 0 for no develop a regression model to predict selling price based on the square footage and number of bedrooms. Use this to predict the selling...
The following data give the selling price, square footage, number of bedrooms, and age of houses...
The following data give the selling price, square footage, number of bedrooms, and age of houses that have sold in a neighborhood in the past 6 months. Develop three regression models to predict the selling price based upon each of the other factors individually. Which of these is best? Selling Price Square Footage Bedrooms Age (Years) 84000 1670 2 30 79000 1339 2 25 91500 1712 3 30 120000 1840 3 40 127500 2300 3 18 132500 2234 3 30...
(House Selling Price) The data below show the selling price, square footage, bedrooms, and age of...
(House Selling Price) The data below show the selling price, square footage, bedrooms, and age of houses that have sold in a neighborhood in the last six months. Selling price Square footage Bedrooms Age 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...
Selling Price Square Footage No. of Bedrooms Age of Condo 64000 1670 2 30 59000 1339...
Selling Price Square Footage No. of Bedrooms Age of Condo 64000 1670 2 30 59000 1339 2 25 61500 1712 3 30 79000 1840 3 40 87500 2300 3 18 92500 2234 3 30 95000 2311 3 19 113000 2377 3 7 115000 2736 4 10 138000 2500 3 1 142500 2500 4 3 144000 2479 3 3 145000 2400 3 1 147500 3124 4 0 144000 2500 3 2 155500 4062 4 10 165000 2854 3 3 State the...
Selling Price (Y) Square Footage (X1 ) Bedrooms (X2 ) Age (X3 ) 84,000 1670 2...
Selling Price (Y) Square Footage (X1 ) Bedrooms (X2 ) Age (X3 ) 84,000 1670 2 30 79,000 1339 2 25 91,500 1712 3 30 120,000 1840 3 40 127,500 2300 3 18 132,500 2234 3 30 145,000 2311 3 19 164,000 2377 3 7 155,000 2736 4 10 168,000 2500 3 1 172,500 2500 4 3 174,000 2479 3 3 Determine a correlation matrix for the above variables. Indicate if any collinearity exists between or among the independent variable....
Effects on Selling Price of Houses Square Feet Number of Bedrooms Age Selling Price 1125 2...
Effects on Selling Price of Houses Square Feet Number of Bedrooms Age Selling Price 1125 2 1 121500 1461 3 4 123600 1527 3 8 158100 1719 4 9 214800 1745 4 9 215500 2197 4 11 255000 2414 4 13 257200 28302830 4 14 262200 30153015 5 14 282400 Determine if a statistically significant linear relationship exists between the independent and dependent variables at the 0.01 level of significance. If the relationship is statistically significant, identify the multiple regression...
SELLING PRICE SQUARE FOOTAGE BEDROOMS AGE (YEARS) 84,000 1,670 2 30 79,000 1,339 2 25 91,500...
SELLING PRICE SQUARE FOOTAGE BEDROOMS AGE (YEARS) 84,000 1,670 2 30 79,000 1,339 2 25 91,500 1,712 3 30 120,000 1,840 3 40 127,500 2,300 3 18 132,500 2,234 3 30 145,000 2,311 3 19 164,000 2,377 3 7 155,000 2,736 4 10 168,000 2,500 3 1 172,500 2,500 4 3 174,000 2,479 3 3 175,000 2,400 3 1 177,500 3,124 4 0 184,000 2,500 3 2 195,500 4,062 4 10 195,000 2,854 3 3 2.) Solve this question by...
ADVERTISEMENT
ADVERTISEMENT
ADVERTISEMENT