Stats: Modeling the World Nasta Edition Grades 9-12
Stats: Modeling the World Nasta Edition Grades 9-12
3rd Edition
ISBN: 9780131359581
Author: David E. Bock, Paul F. Velleman, Richard D. De Veaux
Publisher: PEARSON
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Chapter 8, Problem 21E

(a)

To determine

To explain what the slope of the line says about housing prices and house size.

(a)

Expert Solution
Check Mark

Explanation of Solution

It is given in the question that, a random sample of records of sales of homes gives the price and size of homes. A regression to predict price from size has an R -squared of 71.4% . The residual plot indicated that a linear model is appropriate. And the regression analysis gives the model:

  P^ rice=47.82+0.061Size

Thus, the slope of the line says about housing prices and house size is that price of the house increases by about $0.061×1000 or $61.00 per additional square feet.

(b)

To determine

To find out what price would you predict for a 3000 -square foot house in this market.

(b)

Expert Solution
Check Mark

Answer to Problem 21E

The price of the house is $230.82 thousands or $230820 .

Explanation of Solution

It is given in the question that, a random sample of records of sales of homes gives the price and size of homes. A regression to predict price from size has an R -squared of 71.4% . The residual plot indicated that a linear model is appropriate. And the regression analysis gives the model:

  P^ rice=47.82+0.061Size

Thus, we want to predict the price for a 3000 -square foot house in this market, that is by,

  P^ rice=47.82+0.061Size=47.82+0.061×3000=230.82

Thus, the price of the house is $230.82 thousands or $230820 .

(c)

To determine

To find out what is the asking price and explain what is the $6000 called.

(c)

Expert Solution
Check Mark

Answer to Problem 21E

The asking price is $115020 .

Explanation of Solution

It is given in the question that, a random sample of records of sales of homes gives the price and size of homes. A regression to predict price from size has an R -squared of 71.4% . The residual plot indicated that a linear model is appropriate. And the regression analysis gives the model:

  P^ rice=47.82+0.061Size

It is also given that a real estate agent shows a potential buyer a 1200 square foot home, saying that the asking price is $6000 less than what one would expect to pay for a house of this size. Thus, the asking price will be calculated as:

  P^ rice=47.82+0.061Size=47.82+0.061×1200=121.02 or $121020Asking price=$121020$6000=$115020

Thus, the asking price is $115020 . And $6000 is the residual in this context.

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