AP Stats Unit 2 Test Review

What, if anything, is missing from this description?

• Form

• Direction

• Strength

• Outliers

What is the best description of this relationship?

• Positive Linear Association

• Negative Linear Association

• Nonlinear Association

• No association

Which of these is an appropriate least-squares equation for this model?

• 
• 
• 
• 

What effect(s) would removing this point have?

• The coefficient of determination (r^2) would increase.

• The y-intercept would decrease.

• The correlation coefficient (r) would get closer to -1.

• None of these.

Look at the image to see the question & answer choices.

• A

• B

• C

Interpret the residual for the bunch indicated in the scatterplot above.

• This bunch's storage temperature was 2*C warmer than predicted based on the storage life.

• This bunch's storage temperature was 2*C cooler than predicted based on the storage life.

• This bunch's storage temperature was 2 days longer than predicted based on the storage temperature.

• This bunch's storage temperature was 2 days fewer than predicted based on the storage temperature.

Adrianna gathered data on different schools' winning percentages and the average yearly salary of their head coaches (in millions of dollars) in the years 2000-2011. She then created the following scatterplot and regression line.

The fitted line has a y-intercept of 39.

What is the best interpretation of this y-intercept?

• The model indicates that teams with coaches who had a salary of 0 million $ will average a winning percentage of 39%

• The average winning % was 39%.

• The average salary was 39 million dollars.

• On average, each 1 million dollar increase in salary was associated with a 39% increase in winning percentage.

According to this model, what is the predicted life expectancy of a mammal species whose average heart rate is 60 beats per minute?
You may round your answer to the nearest whole year.

Tags

CCSS.HSF.LE.A.2

What can you conclude from this graph?

• The least squares regression equation overestimates y more often than it underestimates y.

• This is a good model. because all of the residuals are close to the line y=0.

• When x = 5, the least squares regression equation underestimates y.

What is the first mistake in Allie's response?

• Point A is not an outlier.

• Removing this point would strengthen the overall pattern, not weaken it.

• Removing this point would get r closer to -1, not to 0.

• Removing this point would get r closer to 1, not to 0.