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Chapter 3: Q 30. (page 175)

In a scatterplot of the average price of a barrel of oil and the average retail price of a gallon of gas, you expect to see

a. very little association.

b. a weak negative association.

c. a strong negative association.

d. a weak positive association.

e. a strong positive association.

Short Answer

Expert verified

The correct option is (a) very little association.

Step by step solution

01

Given information

A scatterplot illustrating the average retail price of a gallon of gas and the average price of a barrel of oil

02

Explanation

When both variables are independent variables, there is no relationship or association between them. Because the average retail price of a gallon of gasoline and the average price of a barrel of oil are both independent variables. As a result, there would be virtually little correlation between the average retail price of a gallon of gas and the average retail price of a gallon of gasoline. Thus, the correct option is (a).

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Most popular questions from this chapter

Less gas? Refer to Exercise 38.

a. Interpret the slope of the regression line.

b. Does the value of the y intercept have meaning in this context? If so, interpret the y intercept. If not, explain why.

Oh, that smarts! Infants who cry easily may be more easily stimulated than others. This may be a sign of a higher IQ. Child development researchers explored the relationship between the crying of infants 4 to 10 days old and their IQ test scores at age 3 years. A snap of a rubber band on the sole of the foot caused the infants to cry. The researchers recorded the crying and measured its intensity by the number of peaks in the most active 20 seconds. The correlation for these data is r=0.45.16 Interpret the correlation.

It’s still early We expect that a baseball player who has a high batting average in the first month of the season will also have a high batting average for the rest of the season. Using 66 Major League Baseball players from a recent season,33 a least-squares regression line was calculated to predict rest-of-season batting average y from first-month batting average x. Note: A player’s batting average is the proportion of times at-bat that he gets a hit. A batting average over 0.300 is considered very good in Major League Baseball.

a. State the equation of the least-squares regression line if each player had the same batting average the rest of the season as he did in the first month of the season.

b. The actual equation of the least-squares regression line is y^=0.245+0.109x

Predict the rest-of-season batting average for a player who had a 0.200 batting average the first month of the season and for a player who had a 0.400 batting average the first month of the season.

c. Explain how your answers to part (b) illustrate regression to the mean.

More brains Refer to Exercise 20

a. Explain why it isn’t correct to say that the correlation is 0.86g/kg

b. What would happen to the correlation if the variables were reversed on the scatterplot?

Explain your reasoning.

c. What would happen to the correlation if brain weight was measured in kilograms instead of grams? Explain your reasoning.

Longer strides In Exercise 43, we summarized the relationship between x =

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model, technology gives s = 3.50 and r2 = 0.399.

a. Interpret the value of s.

b. Interpret the value of r2.
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