4.07: Quadratic Regression Models

Which quadratic equation fits the data in the table? y=x2−x+3 y=−x2−x−3 y=x2−x−3 y = x² + x + 3

A. y=x2−x+3

Which quadratic regression equation best fits the data set? yˆ=1.87x2−5.16x+10.54 yˆ=1.87x2+5.16x+10.54 yˆ=1.87x2+5.16x yˆ=−1.87x2+5.16x

A. yˆ=1.87x2−5.16x+10.54

The equation p=1.65t2+18.25t+155 approximates the average sale price p of a house (in thousands of dollars) for years t since 2010. What is the best estimate for the price of the house in year 2018? $364,000 $407,000 $427,000 $453,000

B. $407,000

What is the quadratic regression equation for the data set? yˆ=0.056x2−1.278x−0.886 yˆ=0.056x2+1.278x−0.886 yˆ=0.056x2+1.278 yˆ=0.056x2+1.278x

B. yˆ=0.056x2+1.278x−0.886

Which quadratic equation fits the data in the table? y=x2−7x−1 y = x² + 7x + 1 y=x2−7x+1 y=−x2+7x+1

B.y = x² + 7x + 1

The equation p=1.7t2+18.75t+175 approximates the average sale price p of a house (in thousands of dollars) for years t since 2010. What is the best estimate for the price of the house in year 2020? $434,000 $481,000 $533,000 $587,000

C. $533,000

The equation y=−0.065x2+6.875x+6200 models the amount y of sugar (in pounds per square foot) produced where x is the amount of fertilizer (in pounds per square foot) used. What is the best approximate for the amount of sugar produced when 3 pounds per square foot of fertilizer is used? 6200 lb/ft2 6210 lb/ft2 6220 lb/ft2 6230 lb/ft2

C. 6220 lb/ft2

The equation y=−3.5x2−0.5x+65 models the height of a ball in inches for each bounce. What is the best approximate for the height of the ball after the 3rd bounce? 7 in. 14 in. 32 in. 50 in.

C.32

Which quadratic regression equation best fits the data set? yˆ=0.095x2+29.1 yˆ=0.95x2+1.757x+29.1 yˆ=0.095x2+1.757x+29.1 yˆ=0.095x2−1.757x+29.1

D. yˆ=0.095x2−1.757x+29.1

What is the quadratic regression equation for the data set? yˆ=0.056x2+1.278 yˆ=0.056x2+1.278x yˆ=0.056x2−1.278x−0.886 yˆ=0.056x2+1.278x−0.886

D.yˆ=0.056x2+1.278x−0.886