Mathematics, 13.02.2020 23:00 datgamer13
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.
Square Footage, x
Selling Price ($000s), y
2133
369
3052
355.1
1074
181.5
1968
336.9
3062
614.2
2852
382.3
4292
655.7
2186
373.2
2496
407.4
1718
299.8
1718
260.1
3739
679
a) Which variable is the explanatory variable?
___Square Footage
___Selling Price
(b) Draw a scatter diagram of the data. Choose the correct scatter diagram below.
(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?
___Yes
___No
(e) Find the least-squares regression line treating square footage as the explanatory variable.
ModifyingAbove y with caretyequals=nothingxplus+left parenthesis nothing right parenthesis
(Round to two decimal places as needed.)
(f) Interpret the slope. Select the correct choice below and, if necessary, fill in the answer box to complete your choice.
or a house that is 0 square feet, the predicted selling price is nothing thousand dollars.
(Round to two decimal places as needed.)
B. For every additional thousand dollars in selling price, the square footage increases by nothing square feet, on average.
(Round to two decimal places as needed.)
C. For every additional square foot, the selling price
increases by nothing thousand dollars, on average.
(Round to two decimal places as needed.)
D. For a house that is sold for $0, the predicted square footage is
nothing.
Answers: 3
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