Linear, Exponential and Quadratic Regressions

Determine the curve of best fit.

• y = -2.7x + 7.4

• y = 0.95x² - 2.08x - 0.75

• y = -.05x - 3.26

• y = 0.95x² + 2.08x + 0.75

The data in the table represents a linear relationship between altitude and temperature.

• y = -0.14x + 74.88

• y = -0.14x - 74.88

• y = 0.14x + 74.88

• y = -2.35x² - 0.09x + 73.79

Tags

CCSS.8.EE.B.5

Which equation fits the pattern of the following sets of ordered pairs?

• y = -1/2 x + 3

• y = -1/2 x - 3

• y = x + 3

• y = x - 3

Tags

CCSS.6.EE.C.9

The table below gives the number of hours spent studying for a math exam (x) and the exam grade (y). Using a line of best fit, predict the exam grade of a student who studied 5 hours.

• 100

• 93

• 96

• 87

This set of ordered pairs shows a relationship between x and y. Using the line of best fit, which is closest to the output when the input is 3?

• 10.72

• 9.5

• 2.5

• 13

Tags

CCSS.HSF-LE.A.1B

Find the quadratic equation for the relationship of the horizontal distance and the height of the ball. Answers may be rounded to the hundredth.

• y= -0.11x² + 2.11x + 4.21

• y= 2.11x² +4.22x - 0.12

• y=4.22x² -0.12x + 2.11

• y= -0.12x² + 2.11x + 4.22

A person travels by car. They record their miles driven in a data table. Calculate the linear regression equation of this data. Answers may be rounded to the nearest hundredth.

• y = 61.93x - 1.79

• y = -1.79x + 61.93

• y = 61.92x + 1.79

• y = 61.92x -1.78

Tags

CCSS.8.EE.C.8C

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 approximately 62 miles per hour.

• They drove 61.93 miles total.

• They drove 61.93 hours total.

Tags

CCSS.HSF.LE.B.5

A restaurant sells pizza for the prices in the data table. Using the linear regression equation of the data, calculate the cost of a supreme pizza with 9 toppings.

• $25.54

• $25.5429

• $25.50

• $26.00

Using the data plotted on the scatterplot, which equation most closely describes a line of best fit for the data?

• y = 2x - 4

• y = 2x + 5

• y = x + 6

• y + 3x - 4

Tags

CCSS.8.EE.B.5