Logout Open In App
Open In App
Warning: foreach() argument must be of type array|object, bool given in /var/www/html/web/app/themes/studypress-core-theme/template-parts/header/mobile-offcanvas.php on line 20

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).

Unlock Step-by-Step Solutions & Ace Your Exams!

  • Full Textbook Solutions

    Get detailed explanations and key concepts

  • Unlimited Al creation

    Al flashcards, explanations, exams and more...

  • Ads-free access

    To over 500 millions flashcards

  • Money-back guarantee

    We refund you if you fail your exam.

Start your free trial

Over 30 million students worldwide already upgrade their learning with Vaia!

One App. One Place for Learning.

All the tools & learning materials you need for study success - in one app.

Get started for free

Most popular questions from this chapter

Joan is concerned about the amount of energy she uses to heat her home.

The scatterplot shows the relationship between x = mean temperature in a particular month

and y = mean amount of natural gas used per day (in cubic feet) in that month, along with the regression line y^=1425−19.87x

a. Predict the mean amount of natural gas Joan will use per day in a month with a mean temperature of 30°F.

b. Predict the mean amount of natural gas Joan will use per day in a month with a mean temperature of 65°F.

c. How confident are you in each of these predictions? Explain your reasoning.

Heavy backpacks Ninth-grade students at the Webb Schools go on a

backpacking trip each fall. Students are divided into hiking groups of size 8 by selecting names from a hat. Before leaving, students and their backpacks are weighed. The data here are from one hiking group. Make a scatterplot by hand that shows how to backpack weight relates to body weight.

Born to be old? Is there a relationship between the gestational period (time from conception to birth) of an animal and its average life span? The figure shows a scatterplot of the gestational period and average life span for 43 species of animals.

a. Describe the relationship shown in the scatterplot.

b. Point A is the hippopotamus. What effect does this point have on the correlation, the equation of the least-squares regression line, and the standard deviation of the residuals?

c. Point B is the Asian elephant. What effect does this point have on the correlation, the equation of the least-squares regression line, and the standard deviation of the residuals?

A carpenter sells handmade wooden benches at a craft fair every week. Over the past year, the carpenter has varied the price of the benches from \(80

to \)120 and recorded the average weekly profit he made at each selling price. The prices of the bench and the corresponding average profits are shown in the table.

a. Make a scatterplot to show the relationship between price and profit.

b. The correlation for these data is r=0Explain how this can be true even though there is a strong relationship between price and average profit.

Late bloomers? Japanese cherry trees tend to blossom early when spring weather is warm and later when spring weather is cool. Here are some data on the average March temperature (in degrees Celsius) and the day in April when the first cherry blossom appeared over a 24-year period:

a. Make a well-labeled scatterplot that’s suitable for predicting when the cherry trees will blossom from the temperature. Which variable did you choose as the explanatory variable? Explain your reasoning.

b. Use technology to calculate the correlation and the equation of the least-squares regression line. Interpret the slope and y-intercept of the line in this setting.

c. Suppose that the average March temperature this year was 8.2°C. Would you be willing to use the equation in part (b) to predict the date of the first blossom? Explain your reasoning.

d. Calculate and interpret the residual for the year when the average March temperature was 4.5°C.

e. Use technology to help construct a residual plot. Describe what you see.
See all solutions

Recommended explanations on Math Textbooks

Applied Mathematics

Read Explanation

Calculus

Read Explanation

Theoretical and Mathematical Physics

Read Explanation

Probability and Statistics

Read Explanation

Statistics

Read Explanation

Geometry

Read Explanation
View all explanations

What do you think about this solution?

We value your feedback to improve our textbook solutions.

Study anywhere. Anytime. Across all devices.

Sign-up for free