Linear, Quadratic, Cubic, & Quartic Regression

Based on the table, which function can best be used to model this situation?

• h(t) = 99t² + 858

• h(t) = -4.9t² + 295t + 0.6

• h(t) = -4.9t² + 295t + 2

• h(t) = 99t² + 1,470.3

Tags

CCSS.HSA.CED.A.1

CCSS.HSA.SSE.A.1

CCSS.HSF.IF.B.4

Which of the following quadratic equations best represents the following data?

• y = 7x² - 3x

• y = 3x² - 2x + 1

• y = 6x² + 3x - 2

• y = 7x² - 3x + 1

Tags

CCSS.HSA.CED.A.2

CCSS.HSA.SSE.A.1

Find the best fitting quadratic model for the data given.

• 1.2x² + 13x + 504.3
• 12x² + 13x + 504.3
• .12x² + 1.3x + 504.3

Tags

CCSS.HSA.CED.A.2

CCSS.HSA.SSE.A.1

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

Tags

CCSS.8.EE.C.8C

A restaurant sells pizza for the prices in the data table.  Calculate the linear regression equation of the data.

• y = 1.5x + 12
• y = 12x + 1.5
• y = 0.67x - 8
• y = -8x + 0.67

Tags

CCSS.8.EE.C.8C

A person travels by car.  They record their miles driven in a data table.  Calculate the linear regression equation of this data.

• y = 61.93x - 1.79
• y = -1.79x + 61.93
• y = 0.016x + 0.03
• y = 0.03x + 0.016

Tags

CCSS.HSF-LE.A.1B

The annual profits for a company are given in the following table, where x represents the number of years since 1992, and y represents the profit in thousands of dollars. Write the linear regression equation that represents this set of data, rounding all coefficients to the nearest hundredth. Using this equation, estimate the year in which the profits would reach 378 thousand dollars.

• 2029

• 2014

• 2003

• 8753

Tags

CCSS.HSA.CED.A.2

CCSS.HSS.ID.C.7

• $f\left(x\right)=192x^2-16x+0$

• $f\left(x\right)=-16x^2+192x+0$

• $f\left(x\right)=-4.9x^2+5x+19$

• $f\left(x\right)=3.37x^2-1.98x-7$

Tags

CCSS.HSA.APR.A.1

CCSS.HSA.APR.B.3

CCSS.HSA.CED.A.1

CCSS.HSA.REI.B.4

CCSS.HSA.SSE.A.1

Write the exponential regression equation for the data.

• Y=8.16(2.7)^x

• Y=81.6(2.7)^x

• Y=8.16(.27)^x

• Y=8.16(27)^x

Tags

CCSS.HSF.LE.A.1

CCSS.HSF.LE.A.2

CCSS.HSF.LE.B.5

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

Tags

CCSS.HSF.LE.A.2