Elementary Statistics (13th Edition)
13th Edition
ISBN: 9780134462455
Author: Mario F. Triola
Publisher: PEARSON
expand_more
expand_more
format_list_bulleted
Concept explainers
Textbook Question
Chapter 10.4, Problem 10BSC
City Fuel Consumption: Finding the Best Multiple Regression Equation. In Exercises 9-12, refer to the accompanying table, which was obtained using the data from 21 cars listed in Data Set 20 “Car Measurements" in Appendix B. The response (y) variable is CITY (fuel consumption in mi/gal). The predictor (x) variables are WT (weight in pounds), DISP (engine displacement in liters), and HWY (highway fuel consumption in mi/gal).
10. If exactly two predictor (x) variables are to be used to predict the city fuel consumption, which two variables should be chosen? Why?
Expert Solution & Answer
Want to see the full answer?
Check out a sample textbook solutionStudents have asked these similar questions
The St. Lucian Government is interested in predicting the number of weekly riders on the public buses using the following variables:
• • • •
Price of bus trips per weekThe population in the cityThe monthly income of ridersAverage rate to park your personal vehicle
Determine the multiple regression equation for the data.
What is the predicted value of the number of weekly riders if: price of bus trips per week = $24; population = $2,000,000; the monthly income of riders = $13,500; and average rate to park your personal vehicle = $150.
Interpret the coefficient of determination.
The data used is from college campuses. The variables used in the analysis below include: crime, total campus crime; enroll, total
enrollment; police, employed officers. Use the estimated OLS models to answer the questions below:
Model A:
In(crime) = -6.631 + 1.270ln(enroll),
(1.034)
(.110)
.5804
n = 97; R² =
Model B:
In(crime) = -4.794+.923ln(enroll) +.516ln(police),
(.144)
(.149)
(1.112)
n = 97; R² = .632
Using Model A, test the null hypothesis that elasticity of crime with respect to enrollment is unit elastic, i.e. equal to one (against a
two-sided alternative). What is the conclusion of your test using a significance level of .01?
Reject
Fail to reject
O Not enough information.
A doctor has collected data on cholesterol, blood pressure, and weight. She also collected data on the eating habits of the subjects (eg. how many ounces of red meat, fish, dairy products, and chocolate consumed per week) She wants to investigate the relationship between the three measures of health and eating habits. Which statistical test can be best used for this study?
a.Linear Regression
b. Correlation Coefficient
c. Frequency Distribution Table
d. ANOVA
Chapter 10 Solutions
Elementary Statistics (13th Edition)
Ch. 10.1 - Notation Twenty different statistics students are...Ch. 10.1 - Interpreting r For the some two variables...Ch. 10.1 - Global Warming If we find that there is a linear...Ch. 10.1 - Scatterplots Match these values of r with the five...Ch. 10.1 - Bear Weight and Chest Size Fifty-four wild bears...Ch. 10.1 - Casino Size and Revenue The New York Times...Ch. 10.1 - Garbage Data Set 31 Garbage Weight in Appendix B...Ch. 10.1 - Cereal Killers The amounts of sugar (grams of...Ch. 10.1 - Explore! Exercises 9 and 10 provide two data sets...Ch. 10.1 - Explore! Exercises 9 and 10 provide two data sets...
Ch. 10.1 - Outlier Refer to the accompanying...Ch. 10.1 - Clusters Refer to the following Minitab-generated...Ch. 10.1 - Testing for a Linear Correlation. In Exercises...Ch. 10.1 - Testing for a Linear Correlation. In Exercises...Ch. 10.1 - Testing for a Linear Correlation. In Exercises...Ch. 10.1 - Testing for a Linear Correlation. In Exercises...Ch. 10.1 - Testing for a Linear Correlation. In Exercises...Ch. 10.1 - Testing for a Linear Correlation. In Exercises...Ch. 10.1 - Testing for a Linear Correlation. In Exercises...Ch. 10.1 - Testing for a Linear Correlation. In Exercises...Ch. 10.1 - Testing for a Linear Correlation. In Exercises...Ch. 10.1 - Testing for a Linear Correlation. In Exercises...Ch. 10.1 - Testing for a Linear Correlation. In Exercises...Ch. 10.1 - Testing for a Linear Correlation. In Exercises...Ch. 10.1 - Testing for a Linear Correlation. In Exercises...Ch. 10.1 - Testing for a Linear Correlation. In Exercises...Ch. 10.1 - Testing for a Linear Correlation. In Exercises...Ch. 10.1 - Testing for a Linear Correlation. In Exercises...Ch. 10.1 - Appendix B Data Sets. In Exercises 2934, use the...Ch. 10.1 - Appendix B Data Sets. In Exercises 2934, use the...Ch. 10.1 - Appendix B Data Sets. In Exercises 2934, use the...Ch. 10.1 - Appendix B Data Sets. In Exercises 2934, use the...Ch. 10.1 - Appendix B Data Sets. In Exercises 2934, use the...Ch. 10.1 - Appendix B Data Sets. In Exercises 2934, use the...Ch. 10.1 - Transformed Data In addition to testing for a...Ch. 10.1 - Finding Critical r Values Table A-6 lists critical...Ch. 10.2 - Notation Different hotels on Las Vegas Boulevard...Ch. 10.2 - Notation What is the difference between the...Ch. 10.2 - Best-Fit Line a. What is a residual? b. In what...Ch. 10.2 - Correlation and Slope What is the relationship...Ch. 10.2 - Making Predictions. In Exercises 58, let the...Ch. 10.2 - Making Predictions. In Exercises 58, let the...Ch. 10.2 - Making Predictions. In Exercises 58, let the...Ch. 10.2 - Making Predictions. In Exercises 58, let the...Ch. 10.2 - Finding the Equation of the Regression Line. In...Ch. 10.2 - Finding the Equation of the Regression Line. In...Ch. 10.2 - Effects of an Outlier Refer to the Mini...Ch. 10.2 - Effects of Clusters Refer to the Minitab-generated...Ch. 10.2 - Regression and Predictions. Exercises 1328 use the...Ch. 10.2 - Regression and Predictions. Exercises 1328 use the...Ch. 10.2 - Regression and Predictions. Exercises 1328 use the...Ch. 10.2 - Regression and Predictions. Exercises 1328 use the...Ch. 10.2 - Regression and Predictions. Exercises 1328 use the...Ch. 10.2 - Regression and Predictions. Exercises 1328 use the...Ch. 10.2 - Regression and Predictions. Exercises 1328 use the...Ch. 10.2 - Regression and Predictions. Exercises 1328 use the...Ch. 10.2 - Regression and Predictions. Exercises 1328 use the...Ch. 10.2 - Regression and Predictions. Exercises 1328 use the...Ch. 10.2 - Regression and Predictions. Exercises 1328 use the...Ch. 10.2 - Regression and Predictions. Exercises 1328 use the...Ch. 10.2 - Regression and Predictions. Exercises 13-28 use...Ch. 10.2 - Regression and Predictions. Exercises 13-28 use...Ch. 10.2 - Regression and Predictions. Exercises 13-28 use...Ch. 10.2 - Regression and Predictions. Exercises 13-28 use...Ch. 10.2 - Large Data Sets. Exercises 29-32 use the same...Ch. 10.2 - Large Data Sets. Exercises 29-32 use the same...Ch. 10.2 - Large Data Sets. Exercises 29-32 use the same...Ch. 10.2 - Large Data Sets. Exercises 29-32 use the same...Ch. 10.2 - Word Counts of Men and Women Refer to Data Set 24...Ch. 10.2 - Earthquakes Refer lo Data Set 21 Earthquakes in...Ch. 10.2 - Least-Squares Property According to the...Ch. 10.3 - se Notation Using Data Set 1 Body Data in Appendix...Ch. 10.3 - Prediction Interval Using the heights and weights...Ch. 10.3 - Coefficient of Determination Using the heights and...Ch. 10.3 - Standard Error of Estimate A random sample of 118...Ch. 10.3 - Interpreting the Coefficient of Determination. In...Ch. 10.3 - Interpreting the Coefficient of Determination. In...Ch. 10.3 - Interpreting the Coefficient of Determination. In...Ch. 10.3 - Interpreting the Coefficient of Determination. In...Ch. 10.3 - Interpreting a Computer Display. In Exercises...Ch. 10.3 - Interpreting a Computer Display. In Exercises...Ch. 10.3 - Interpreting a Computer Display. In Exercises...Ch. 10.3 - Interpreting a Computer Display. In Exercises...Ch. 10.3 - Finding a Prediction Interval. In Exercises 13-16,...Ch. 10.3 - Finding a Prediction Interval. In Exercises 13-16,...Ch. 10.3 - Finding a Prediction Interval. In Exercises 13-16,...Ch. 10.3 - Finding a Prediction Interval. In Exercises 13-16,...Ch. 10.3 - Variation and Prediction Intervals. In Exercises...Ch. 10.3 - Variation and Prediction Intervals. In Exercises...Ch. 10.3 - Variation and Prediction Intervals. In Exercises...Ch. 10.3 - Variation and Prediction Intervals. In Exercises...Ch. 10.3 - Confidence Interval for Mean Predicted Value...Ch. 10.4 - Terminology Using the lengths (in.). chest sizes...Ch. 10.4 - Best Multiple Regression Equation For the...Ch. 10.4 - Adjusted Coefficient of Determination For Exercise...Ch. 10.4 - Interpreting R2 For the multiple regression...Ch. 10.4 - Interpreting a Computer Display. In Exercises 5-8,...Ch. 10.4 - Interpreting a Computer Display. In Exercises 5-8,...Ch. 10.4 - Interpreting a Computer Display. In Exercises 5-8,...Ch. 10.4 - Interpreting a Computer Display. In Exercises 5-8,...Ch. 10.4 - City Fuel Consumption: Finding the Best Multiple...Ch. 10.4 - City Fuel Consumption: Finding the Best Multiple...Ch. 10.4 - City Fuel Consumption: Finding the Best Multiple...Ch. 10.4 - City Fuel Consumption: Finding the Best Multiple...Ch. 10.4 - Appendix B Data Sets. In Exercises 13-16, refer to...Ch. 10.4 - Prob. 14BSCCh. 10.4 - Appendix B Data Sets. In Exercises 13-16, refer to...Ch. 10.4 - Appendix B Data Sets. In Exercises 13-16, refer to...Ch. 10.4 - Testing Hypotheses About Regression Coefficients...Ch. 10.4 - Confidence Intervals for a Regression Coefficients...Ch. 10.4 - Dummy Variable Refer to Data Set 9 Bear...Ch. 10.5 - Identifying a Model and R2 Different samples are...Ch. 10.5 - Super Bowl and R2 Let x represent years coded as...Ch. 10.5 - Super Bowl and R2 Let x represent years coded as...Ch. 10.5 - Interpreting a Graph The accompanying graph plots...Ch. 10.5 - Finding the Best Model. In Exercises 5-16,...Ch. 10.5 - Finding the Best Model. In Exercises 5-16,...Ch. 10.5 - Finding the Best Model. In Exercises 5-16,...Ch. 10.5 - Finding the Best Model. In Exercises 5-16,...Ch. 10.5 - Finding the Best Model. In Exercises 5-16,...Ch. 10.5 - Finding the Best Model. In Exercises 5-16,...Ch. 10.5 - Finding the Best Model. In Exercises 5-16,...Ch. 10.5 - Finding the Best Model. In Exercises 5-16,...Ch. 10.5 - Finding the Best Model. In Exercises 5-16,...Ch. 10.5 - Finding the Best Model. In Exercises 5-16,...Ch. 10.5 - Finding the Best Model. In Exercises 5-16,...Ch. 10.5 - Finding the Best Model. In Exercises 5-16,...Ch. 10.5 - Sum of Squares Criterion In addition to the value...Ch. 10 - The following exercises are based on the following...Ch. 10 - The following exercises are based on the following...Ch. 10 - The following exercises are based on the following...Ch. 10 - The following exercises are based on the following...Ch. 10 - The following exercises are based on the following...Ch. 10 - The following exercises are based on the following...Ch. 10 - The following exercises are based on the following...Ch. 10 - The following exercises are based on the following...Ch. 10 - The following exercises are based on the following...Ch. 10 - Interpreting Scatterplot If the sample data were...Ch. 10 - Cigarette Tar and Nicotine The table below lists...Ch. 10 - 2. Cigarette Nicotine and Carbon Monoxide Refer to...Ch. 10 - Time and Motion In a physics experiment at Doane...Ch. 10 - 4. Multiple Regression with Cigarettes Use the...Ch. 10 - Stocks and Sunspots. Listed below are annual high...Ch. 10 - Stocks and Sunspots. Listed below are annual high...Ch. 10 - Stocks and Sunspots. Listed below are annual high...Ch. 10 - Stocks and Sunspots. Listed below are annual high...Ch. 10 - Stocks and Sunspots. Listed below are annual high...Ch. 10 - Cell Phones and Driving In the authors home town...Ch. 10 - Ages of Moviegoers The table below shows the...Ch. 10 - Ages of Moviegoers Based on the data from...Ch. 10 - Speed Dating Data Set 18 Speed Dating" in Appendix...Ch. 10 - Speed Dating Data Set 18 Speed Dating" in Appendix...Ch. 10 - Speed Dating Data Set 18 Speed Dating" in Appendix...Ch. 10 - Speed Dating Data Set 18 Speed Dating" in Appendix...Ch. 10 - Speed Dating Data Set 18 Speed Dating in Appendix...Ch. 10 - Speed Dating Data Set 18 Speed Dating in Appendix...Ch. 10 - Critical Thinking: Is the pain medicine Duragesic...Ch. 10 - Critical Thinking: Is the pain medicine Duragesic...Ch. 10 - Critical Thinking: Is the pain medicine Duragesic...Ch. 10 - Critical Thinking: Is the pain medicine Duragesic...Ch. 10 - Critical Thinking: Is the pain medicine Duragesic...
Knowledge Booster
Learn more about
Need a deep-dive on the concept behind this application? Look no further. Learn more about this topic, statistics and related others by exploring similar questions and additional content below.Similar questions
- Find the equation of the regression line for the following data set. x 1 2 3 y 0 3 4arrow_forwardFor the following exercises, use Table 4 which shows the percent of unemployed persons 25 years or older who are college graduates in a particular city, by year. Based on the set of data given in Table 5, calculate the regression line using a calculator or other technology tool, and determine the correlation coefficient. Round to three decimal places of accuracyarrow_forwardLife Expectancy The following table shows the average life expectancy, in years, of a child born in the given year42 Life expectancy 2005 77.6 2007 78.1 2009 78.5 2011 78.7 2013 78.8 a. Find the equation of the regression line, and explain the meaning of its slope. b. Plot the data points and the regression line. c. Explain in practical terms the meaning of the slope of the regression line. d. Based on the trend of the regression line, what do you predict as the life expectancy of a child born in 2019? e. Based on the trend of the regression line, what do you predict as the life expectancy of a child born in 1580?2300arrow_forward
- What does the y -intercept on the graph of a logistic equation correspond to for a population modeled by that equation?arrow_forwardD& T LTD marketing team needed more information about the effectiveness of their 3 main mode of advertising. To determine which type is the most effective, the manager collected one week’s data from 25 randomly selected stores. For each store, the following variables were recorded: Weekly gross sales Weekly expenditure on direct mailing (Direct) Weekly expenditure on newspaper advertising (Newspaper) Weekly expenditure on television commercials (Television) Following is the regression output based on the above-mentioned data. SUMMARY OUTPUT Regression Statistics Multiple R 0.442…arrow_forwardBill wants to explore factors affecting work stress. He would like to examine the relationship between age, number of years at the workplace, perceived social support, and work stress. He collects data on the variables from 100 employees (males and females) working in banks. Conduct a multiple regression analysis to answer the following questions: What is the relationship of age, number of years, and social support with work stress? Is the regression significant? If yes, what does it indicate? What is the regression equation for all the predictors? Write a results section based on your analysis that answers the research question. * last person got this wrong*arrow_forward
- Beachcomber Ltd in a local car dealership that sells used and new vehicles. The manager of the company wants to know how different variables affect the sales of his vehicles. A random sample of yearly data was taken with the view to testing the model: SALES=?+?AGE+?MIL+?ENG Where SALES= amount that a vehicle is sold for($000’s), AGE = age of the vehicle, MIL= the total mileage of the vehicle at the point of sale and ENG = the size of the engine. The sample of data was processed using MINITAB and the following is an extract of the output obtained: d) Hence test whether ? is significant. Give reasons for your answer. e) Perform the F Test making sure to state the null and alternative hypothesis. f) Given an interpretation of the term “R-sq” and comment on its value.arrow_forwardBeachcomber Ltd in a local car dealership that sells used and new vehicles. The manager of the company wants to know how different variables affect the sales of his vehicles. A random sample of yearly data was taken with the view to testing the model: SALES=?+?AGE+?MIL+?ENG Where SALES= amount that a vehicle is sold for($000’s), AGE = age of the vehicle, MIL= the total mileage of the vehicle at the point of sale and ENG = the size of the engine. The sample of data was processed using MINITAB and the following is an extract of the output obtained: a) What is dependent and independent variables? b) Fully write out the regression equation c) Fill in the missing values ‘*’, ‘**’, and ‘***’.arrow_forwardLillian conducted a small survey of her friends and family. She asked them how many hours per week they spend reading digital documents (newspapers, blogs, books, etc.), and their age. She created the scatter plot below with the results she obtained. Draw the regression line that best represents this scatter plot and determine its equation.arrow_forward
- Let price denote a price index for the goods sold by a restaurant, advert the amount spent on advertising, sales the sales for the restaurant, and consider the following two regressions First regression: sales = B1 + B2price + B3price? + B4advert + ßsadvert? + e, Second regression: sales = B1 + B2price + B3price? + e We estimate both regressions using a sample of 105 observations. The sum of square residuals (E ê) from the first regression equals 50, while the sum of square Li=1 residuals from the second regression equals 70. Suppose we are interested in testing the null hypothesis that expected sales do not depend on advertising. What is the F- statistic for this null hypothesis? Recall the F-statistic is given by ((SSER - SSEU)/J)/(SSEy/(n – K)). O a. -15 O b. 42 Oc. 21 O d. 20 O e. All other options are incorrect.arrow_forwardA magazine publishes restaurant ratings for various locations around the world. The magazine rates the restaurants for food, decor, service, and the cost per person. Develop a regression model to predict the cost per person, based on a variable that represents the sum of the three ratings. The magazine has compiled the accompanying table of this summated ratings variable and the cost per person for 25 restaurants in a major city. Complete parts (a) through (e) below. Click the icon to view the table of summated ratings and cost per person. ..... a. Construct a scatter plot. Choose the correct graph below. A. Ов. С. D. ACost ($) 90- ACost ($) 90- ACost ($) 90- ACost ($) 90- 0- 0- 90 90 90 90 Rating Rating Rating Rating b. Assuming a linear relationship, use the least-squares method to compute the regression coefficients b, and b,. bo = and b, (Round to two decimal places as needed.) c. Interpret the meaning of the Y-intercept, bo, and the slope, b,. Choose the correct answer below. O A.…arrow_forwardA magazine publishes restaurant ratings for various locations around the world. The magazine rates the restaurants for food, decor, service, and the cost per person. Develop a regression model to predict the cost per person, based on a variable that represents the sum of the three ratings. The magazine has compiled the accompanying table of this summated ratings variable and the cost per person for 25 restaurants in a major city. Complete parts (a) through (e) below. Click the icon to view the table of summated ratings and cost per person. a. Construct a scatter plot. Choose the correct graph below. O A. Ов. OC. OD. ACost ($) 90- Q A Cost ($) 904 A Cost ($) 90- ACost ($) 90- 0- 0- 0- 0- 90 Rating 90 Rating 90 90 Rating Rating Summated ratings and cost per person b. Assuming a linear relationship, use the least-squares method to compute the regression coefficients bo and b,. bo =D and b, =O (Round to two decimal places as needed.) Summated Rating Cost ($ per person)|9 c. Interpret the…arrow_forward
arrow_back_ios
SEE MORE QUESTIONS
arrow_forward_ios
Recommended textbooks for you
- Glencoe Algebra 1, Student Edition, 9780079039897...AlgebraISBN:9780079039897Author:CarterPublisher:McGraw HillFunctions and Change: A Modeling Approach to Coll...AlgebraISBN:9781337111348Author:Bruce Crauder, Benny Evans, Alan NoellPublisher:Cengage Learning
- Big Ideas Math A Bridge To Success Algebra 1: Stu...AlgebraISBN:9781680331141Author:HOUGHTON MIFFLIN HARCOURTPublisher:Houghton Mifflin Harcourt
Glencoe Algebra 1, Student Edition, 9780079039897...
Algebra
ISBN:9780079039897
Author:Carter
Publisher:McGraw Hill
Functions and Change: A Modeling Approach to Coll...
Algebra
ISBN:9781337111348
Author:Bruce Crauder, Benny Evans, Alan Noell
Publisher:Cengage Learning
Big Ideas Math A Bridge To Success Algebra 1: Stu...
Algebra
ISBN:9781680331141
Author:HOUGHTON MIFFLIN HARCOURT
Publisher:Houghton Mifflin Harcourt
Correlation Vs Regression: Difference Between them with definition & Comparison Chart; Author: Key Differences;https://www.youtube.com/watch?v=Ou2QGSJVd0U;License: Standard YouTube License, CC-BY
Correlation and Regression: Concepts with Illustrative examples; Author: LEARN & APPLY : Lean and Six Sigma;https://www.youtube.com/watch?v=xTpHD5WLuoA;License: Standard YouTube License, CC-BY