document.write( "Question 1150472: A real estate analyst has developed a multiple regression line, y = 60 + 0.068 x1 - 2.5 x2, to predict y = the market price of a home (in $1,000s), using independent variables, x1 = the total number of square feet of living space, and x2 = the age of the house in years. The regression coefficient of x1 suggests this: __________.\r
\n" ); document.write( "\n" ); document.write( "A)The addition of 1 square foot area of living space results in a predicted increase of $0.068 in the price of the home for homes of different ages
\n" ); document.write( "B)The addition of 1 square foot area of living space results in a predicted increase of $68.00 in the price of the home with the age of the home allowed to vary
\n" ); document.write( "C)The addition of 1 square foot area of living space results in a predicted increase of $68.00 in the price of the home if the age of the home were held constant
\n" ); document.write( "D)The addition of 1 square foot area of living space results in a predicted increase of $0.068 in the price of the home if the age of the home were held constant \r
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Algebra.Com's Answer #772079 by greenestamps(13216)\"\" \"About 
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\n" ); document.write( "Keeping x2 (the age of the house) constant, the value of y (price of the home) increases by 0.068 thousands of dollars for each increase of 1 square foot of living space.

\n" ); document.write( ".068 thousands of dollars is $68.

\n" ); document.write( "ANSWER C

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