Workshop: Correlation and Regression

Estimate the correlation coefficient for this scatterplot.

• A) r = 1.2

• B) r = 0.89

• C)r = 0

• D) r = -0.89

Tags

CCSS.HSS.ID.B.6

CCSS.HSS.ID.C.8

Estimate the correlation coefficient for this scatterplot.

• A) r = -0.9

• B) r = 1

• C) r = 0.9

• D) r = -1

Tags

CCSS.HSS.ID.B.6

CCSS.HSS.ID.C.8

Which of the following is the least–square regression line for this data?

• y = 3.85 – 0.01x

• y = 4.09 – 0.32x

• y = 6.30 – 0.59x

• y = 8.18 – 0.64x

Is this a positive, negative, or no relationship?

• positive relationship

• negative relationship

• no relationship

Tags

CCSS.HSS.ID.B.6

CCSS.HSS.ID.C.7

CCSS.HSS.ID.C.8

Is this a positive, negative, or no relatioship?

• Positive relationship

• Negative relationship

• No relationship

Tags

CCSS.HSS.ID.B.6

CCSS.HSS.ID.C.8

Is r = -0.87 strong, moderate, or weak?

• strong

• moderate

• weak

Tags

CCSS.HSS.ID.B.6

CCSS.HSS.ID.C.8

If x is temperature and y is coffee sales, use the following formula to determine the coffee sales on a 34° day.

y = -60x+6443

• $4584

• $4673

• $8303

• $4403

The linear regression equation for the data is  y = 1.5x + 12.  Interpret the slope of the equation.

• The slope is (0, 1.5).  It means that a pizza with 0 toppings will cost $1.50.
• The slope is 1.5.  It means that it costs $1.50 per topping.
• There are 1.5 toppings.
• There are 1.5 pizzas.

Tags

CCSS.HSF.LE.B.5

CCSS.HSS.ID.C.7

Using your linear regression, what is y when x is 30?

• 61.59
• 52.46
• 57.94
• 59.76

Tags

CCSS.HSA.CED.A.2

CCSS.HSS.ID.C.7

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.HSA.CED.A.2

CCSS.HSA.REI.B.3

CCSS.HSA.SSE.A.1

CCSS.HSS.ID.C.7