Statistics Review Part 1

Data was collected on the weight of a male  laboratory rat for the first 25 weeks after its birth. The linear regression equation is 
y= 40x+100, where x is number of weeks and y is weight in grams. 
What does the y-intercept mean in context of the problem?

• The predicted weight of the rat in year 0. 
• The predicted weight of the rat at birth. 
• The current weight of the rat. 
• The average increase in the rat's weight. 

Tags

CCSS.HSS.ID.C.7

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.

Tags

CCSS.HSF.LE.B.5

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

The scatter plot below shows the number of books read by students in Mrs. Hall’s English class and their final grades. Which statement represents the best description about the line of best fit?

• The more books students read, the lower their English grade.

• The more books students read, the higher their English grade.

• The fewer books students read, the higher their English grade.

• No relationship exists between the number of books students read and their English grades.

Tags

CCSS.HSF.LE.B.5

Which with is the line of best fit?

• A) Black

• B) Orange

• C) Red

• D) Blue

Tags

CCSS.8.EE.B.5

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

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

HINT: you can make a table of values from your points and put them into your calculator in L1 and L2

• y = -5/2x + 20
• y = -x + 19
• y = x + 20
• y = 2/3x + 15 

Write the equation for the linear regression shown.

• $y=ax+b$

• $y=0.6x+0.1$

• $y=0.72x+r$

• $y=0.1x+0.6$

Tags

CCSS.8.EE.B.5

What is the correlation coefficient for the screen shown?