One of the biggest factors in determining the value of a home is the square footage. The accompanying data represent the square footage and selling price​ (in thousands of​ dollars) for a random sample of homes for sale in a certain region. Complete parts​ (a) through​ (h) below.   ​(a) Which variable is the explanatory​ variable?   A. Selling Price   B. Square Footage   ​(c) Determine the linear correlation coefficient between square footage and asking price.   r=_____? ​(Round to three decimal places as​ needed.)   (d) Is there a linear relation between square footage and asking​ price?     No   Yes

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One of the biggest factors in determining the value of a home is the square footage. The accompanying data represent the square footage and selling price​ (in thousands of​ dollars) for a random sample of homes for sale in a certain region. Complete parts​ (a) through​ (h) below.
 
​(a) Which variable is the explanatory​ variable?
 
A. Selling Price
 
B. Square Footage
 
​(c) Determine the linear correlation coefficient between square footage and asking price.
 
r=_____?
​(Round to three decimal places as​ needed.)
 
(d) Is there a linear relation between square footage and asking​ price?
 
 
No
 
Yes
 
(e) Find the​ least-squares regression line treating square footage as the explanatory variable.
 
y=_____x+____
​(Round the slope to three decimal places as needed. Round the intercept to one decimal place as​ needed.)
 
 
​(f) Interpret the slope. Select the correct choice below​ and, if​ necessary, fill in the answer box to complete your choice.
 
A. For every additional thousand dollars in selling​ price, the square footage
increases by ____ square​ feet, on average.
​(Round to three decimal places as​ needed.)
 
B. For a house that is sold for​ $0, the predicted square footage is ​_____
(Round to three decimal places as​ needed.)
 
C. For every additional square​ foot, the selling price increases by _____
thousand​ dollars, on average.
​(Round to three decimal places as​ needed.)
 
D.For a house that is 0 square​ feet, the predicted selling price is ____
thousand dollars.
​(Round to three decimal places as​ needed.)
 
E. It is not appropriate to interpret the slope.
 
​(g) Is it reasonable to interpret the​ y-intercept? Why? Select the correct choice below​ and, if​ necessary, fill in the answer box to complete your choice.
 
A. No—a house of ____ square feet is not possible.
​(Type an integer or a simplified​ fraction.)
 
B.Yes—a house of ____ square feet is possible and within the scope of the model.
​(Type an integer or a simplified​ fraction.)
 
C.No—a house of ____ square feet is not possible and outside the scope of the model.
​(Type an integer or a simplified​ fraction.)
 
D. No—a house of ____ square feet is outside the scope of the model
​(Type an integer or a simplified​ fraction.)
 
E.More information about the houses is necessary before deciding.
 
One home that is 1414 square feet is sold for ​$270 thousand. Is this​ home's price above or below average for a home of this​ size?
 
The​ home's price is above or below the average price. The average price of a home that is 1414 square feet is ____ thousand.
​(Round to the nearest whole number as​ needed.)
Square Footage, x
Selling Price ($000s), y 3
2208
380.4
3239
384.6
1113
187.8
2019
344.8
2970
599.2
2636
4012
349.9
612.2
2203
375.7
2608
424.8
1632
286.2
1816
275.6
3813
689.5
Transcribed Image Text:Square Footage, x Selling Price ($000s), y 3 2208 380.4 3239 384.6 1113 187.8 2019 344.8 2970 599.2 2636 4012 349.9 612.2 2203 375.7 2608 424.8 1632 286.2 1816 275.6 3813 689.5
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