Bivariate Data Regression Review

The scatterplot shows data for nine french fry orders. A tenth fast food chain has been added, as indicated by the arrow. How would this tenth data point affect the slope and correlation in this scenario?

• Slope decreases, correlation increases

• Slope increases, correlation increases

• Slope increases, correlation decreases

• Slope decreases, correlation decreases

• Cannot be determined without the full set of data

Battery life has a strong, negative, linear relationship with temperature. If the least-squares regression line using x = temperature explains 90% of the variation in battery life, which of the following must be the correlation, r, between battery life and temperature?

• -0.90

• 0.90

• -0.95

• 0.95

• Cannot be determined without the original data.

Tags

CCSS.HSF.LE.B.5

Using the least-squares regression line, ˆy = −25.5+1.5x , what is the residual for the data point at (28,19)?

• -2.5

• 2.5

• 4.33

• 16.5

• 19

Would the linear model be appropriate?

• YES

• NO

Tags

CCSS.HSF-LE.A.1B

Can you predict the battery life of a tablet using the price? Using the data from a sample of 15 tablets, the LSRL y-hat=4.67 + 0.0068x was calculated using x=price in dollars and y= battery life in hours. S=1.21 and r²=0.342. Which is the correct interpretation of the coefficient of determination.

• 34.2% of the variability in battery life is explained by the LSRL with x=price in dollars.

• The actual battery life in hours is typically 1.21 hours away from the battery life predicted by the LSRL

• There is a weak positive linear association between price in dollars and battery life.

• We predict the battery life of a tablet will increase 0.0068 hours for each increase of $1 in price

• 50 miles

• -50 miles

• 8 miles

• -25 miles

Tags

CCSS.8.EE.C.8C

LSRL stands for

• Least Sum Regression Line

• Least Squares Regression Line

• Lower Standard Regression Line

• Line Scatterplot Regression Line

Which of the following relationships between two variables could be described using correlation, r?

• Number of books read and gender of a student.

• Number of football games played and the position of a football player.

• High temperature of the day and number of zoo visitors that day.

• Type of beverage ordered and time of day it was ordered.

• Brand of cell phone and number of cell phones sold.

• This residual graph represents a linear fit.
• This graph represents a nonlinear fit.
• This residual graph represents no fit.

In a scatterplot r is called

• Coefficient of Determination

• Correlation coefficient

• Regression Line

• Slope