M1T3 Review - Linear Regression

Which graph most clearly shows a negative correlation between the x- and y−values?

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Tags

CCSS.HSS.ID.B.6

Which graph most clearly shows a no correlation between the x- and y−values?

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Tags

CCSS.HSS.ID.B.6

CCSS.HSS.ID.C.9

Which graph most clearly shows a positive correlation between the x- and y−values?

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Tags

CCSS.HSS.ID.B.6

What does a correlation coefficient of r=−0.01

imply about the graph of a data set? Select all that apply.

• A linear model is not a good fit for the data.

• A linear model is a good fit for the data.

Tags

CCSS.HSS.ID.C.8

Which correlation coefficient is most accurate for this data set?

• r = - 0.3

• r = 0.99

• r = -0.99

Tags

CCSS.HSS.ID.B.6

CCSS.HSS.ID.C.8

Determine the linear regression equation for the data set. Use desmos table and the formula  $y_1\sim mx_1+b$  

• y=20.8x-35

• y=-35x+20.8

• y=.99x-35

• y=.98x+.99

Tags

CCSS.HSA.CED.A.2

CCSS.HSA.REI.D.10

CCSS.HSF.IF.B.4

CCSS.HSF.IF.B.6

CCSS.HSF.IF.C.7

CCSS.HSS.ID.B.6

CCSS.HSS.ID.C.7

CCSS.HSS.ID.C.8

Determine the correlation coefficient for the data set. Use desmos table and the formula
   $y_1\sim mx_1+b$  

• r=.99

• r=.98

• r=20.7

• r=-35

Tags

CCSS.HSS.ID.C.8

The linear regression equation that best represents the line of best fit for the data is y=20.8x-35. What does the slope represent?

• The number of bacteria increase by 20.8 per hour

• The number of bacteria increase by 20.8 per minute

• The number of bacteria decrease by 35 per hour

• The number of bacteria decrease by 35 per minute

Tags

CCSS.HSS.ID.C.7

The linear regression equation that best represents the line of best fit for the data is y=20.8x-35. Use the equation to predict the number of bacteria in 24 hours.

• 35

• 277

• 464

• 819

Tags

CCSS.HSF.IF.B.4

CCSS.HSF.IF.B.5

CCSS.HSS.ID.C.7