Linear, Exponential, and Quadratic Regression

What is the line of best fit?

• f(x)= 5x+1.82

• cannot be determined

• f(x)= 1.82x + 5.02

• f(x)= 1.1x + 4.2

The linear regression equation is y = 61.93x - 1.79.  Use the equation to predict how far this person will travel after 10 hours of driving.

• 10 miles

• 617.5 miles

• 0.19 miles

• 500 miles

Which of the following could be a possible line of best fit for the data?

• y = -5/2x + 20

• y = -x + 19

• y = x + 20

• y = 2/3x + 15 

Use the exponential regression to find an equation that fits the​ data, where x is the years since 1990.

• y=8.92•1.23^x

• y=1.23•8.92^x

• y=8.92+1.23x

• y=8.92x+1.23

Which type of regression model does the scatter plot appear to show?

• linear

• exponential

• quadratic

The linear regression equation is y = 61.93x - 1.79.  According to the model, the slope can be interpreted as:

• After 0 hours of driving, they went 61.93 miles.

• They drove at a speed of 61.93 miles per hour.

• They drove 61.93 miles total.

• They drove 61.93 hours total.

Find the quadratic equation for the relationship of the horizontal distance and the height of the ball.

• y= -18x² + 2.11x + 4.21

• y= -.06x² +1.06x + 7.9

• y= -6x² +1.06x + 79

• y= -.12x² + 2.11x + 4.22

A chemist has a 100-gram sample of a radioactive material. He records the amount of radioactive material every week for 6 weeks and obtains the following data. Determine the exponential regression that best models these data.

• y = 100(8.7)^x

• y = 100(1.87)^x

• y = 100(.87)^x

• y = 100(.13)^x

Which of the following is the exponential regression equation for this data?

• Y = 8.16(2.7)^X

• Y = 81.6(2.7)^X

• Y = 8.16(.27)^X

• Y = 8.16(27)^X

A scientist observes the weight, y, of a 100-gram sample decay every week, x. Determine which exponential regression best models the data in the table.

• y = 100(8.7)^x

• y = 100(1.87)^x

• y = 100(.87)^x

• y = 100(.13)^x