AP Stats Chapter 3

Write the linear regression equation for the data set foot length (x) and height (y).

• yhat = 28.93 + 1.155x

• height = 28.39(foot length) + 1.155

• yhat = 1.878 + 117.99x

• height = 117.99 + 1.878(foot length)

What is the correlation value?

• .209

• .457

• .13

• .361

The following scatterplot describes the relationship between height (in cm) and foot length (also in cm) for 12 randomly selected students from the British Census @ Schools database. Which of the following is the best description of this relationship?

• There is some random variation, but otherwise height is directly proportional to foot length.

• There is a roughly linear relationship between height and foot length.

• There is a moderately weak, positive linear relationship between height and foot length.

• The relationship between height and foot length is linear, positive, and very strong.

One of the following is a correct statement involving correlation. The other three contain blunders. Which one is correct? 

• The correlation between the gas mileage of a car and its weight is r = -0.71 gallon-pounds.

• The correlation between GPA and hours of sleep per night is r = 1.06.

• There is a correlation of r = 0.54 between the position a football player plays and his or her weight.

• The correlation between amount of fertilizer and pounds of tomatoes harvested was found to be r = 0.33.

If you graphed height as the explanatory variable and weight as the response variable, what would happen to the LSRL and r if you had accidently graphed the weight as the explanatory variable and the height as the response variable?

• LSRL would be different and r would be different

• LSRL would be different and r would stay the same

• LSRL would stay the same and r would be different

• LSRL would stay the same and r would stay the same

For a particular value of an explanatory variable, the residual is -0.7. Which of the following is a true statement?

• The regression line underestimates the actual response variable value at this point.

• The regression line overestimates the actual response variable value at this point.

• . A non-linear regression would provide a better fit.

Mathematical Equivalence

ON

Each of the following two histograms represents the distribution of acceptance rates (percent accepted) among 25 business schools in 1995. The histograms use different class intervals but are based on the same data. In each class interval, the left endpoint is included but not the right. What percent of the schools have an acceptance rate of less than 20%?

• 3%

• 4%

• 12%

• 16%

• 20%

This is a standard deviation contest. Which of the following sets of four numbers has the largest possible standard deviation?

• 7, 8, 9, 10

• 1, 2, 9, 10

• 0, 0, 10, 10

• 0, 1, 2, 3

• 5, 5, 5, 5

Birth weights at a local hospital have a normal distribution with a mean of 110 ounces and a standard deviation of 15 ounces. The proportion of infants with birthweights between 125 ounces and 140 ounces is:

• 0.819

• 0.636

• 0.477

• 0.158

• 0.136