Elementary Statistics (13th Edition)
13th Edition
ISBN: 9780134462455
Author: Mario F. Triola
Publisher: PEARSON
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Chapter 10.1, Problem 31BSC
Appendix B Data Sets. In Exercises 29–34, use the data from Appendix B to construct a
31 CSI Statistics Use all of the shoe print lengths and heights of the 19 males from Data Set 2 “Foot and Height” in Appendix B.
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Cigarette Tar and Nicotine The table below lists measured amounts (mg) of tar, carbon monoxide (CO), and nicotine in king size cigarettes of different brands (from Data Set 13 “Cigarette Contents” in Appendix B).
a. Is there is sufficient evidence to support a claim of a linear correlation between tar and nicotine?
b. What percentage of the variation in nicotine can be explained by the linear correlation between nicotine and tar?
c. Letting y represent the amount of nicotine and letting x represent the amount of tar, identify the regression equation.
d. The Raleigh brand king size cigarette is not included in the table, and it has 23 mg of tar. What is the best predicted amount of nicotine? How does the predicted amount compare to the actual amount of 1.3 mg of nicotine?
construct a scatterplot, and find the value of the linear correlation coefficient r. Also find the P-value or the critical values of r from Table A-6 using α = 0.05 Determine whether there is sufficient evidence to support a claim of a linear correlation between the two variables. (Save your work because the same data sets will be used in Section 10-3 exercises.)
Crickets and Temperature One classic application of correlation involves the association between the temperature and the number of times a cricket chirps in a minute. Listed below are the numbers of chirps in 1 min and the corresponding temperatures in °F (based on data from The Song of Insects by George W. Pierce, Harvard University Press). Is there sufficient evidence to conclude that there is a linear correlation between the number of chirps in 1 min and the temperature?
a) Calculate the sample correlation coefficient r (show all your work).b) Calculate the regression line (you may use technology, but you should write up the details).c) Use the regression line obtain in b. to predict the value of y for x = 0.3 year.d) Use the regression line obtain in b. to predict the value of y for x = 0.8 year.
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...
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- A statistical program is recommended. A study of emergency service facilities investigated the relationship between the number of facilities and the average distance traveled to provide the emergency service. The following table gives the data collected. Number of Facilities Average Distance (miles) 9 1.65 11 1.11 16 0.84 21 0.62 27 0.50 30 0.48 (a) Develop a scatter diagram for these data, treating average distance traveled as the dependent variable. 1.8- 1.8 1.8 35 1.6- 1.6 1.6 30 1.4 1.4 1.4 1.2 1.2 1.2 25 1. 1. 1. 20 0.8- 0.8 0.8 0.6- 0.6 0.6- 15 0.4 0.4- 0.4 10 0.2- 0.2 0.2 0. 0. 0. 10 15 20 25 30 35 10 15 20 25 30 35 10 15 20 25 30 35 0. 0.2 0.4 0.6 0,8 1. 1.2 1.4 1.6 1.8 Number Number Number Distance (b) Does a simple linear regression model appear to be appropriate? Explain. O No, the scatter diagram suggests that there is a curvilinear relationship. O Yes, the scatter diagram suggests that there is a linear relationship. O No, the scatter diagram suggests that there is no…arrow_forwardTesting for a Linear Correlation. In Exercises 13–28, construct a scatterplot, and find the value of the linear correlation coefficient r. Also find the P-value or the critical values of r from Table A-6. Use a significance level of α = 0.05. Determine whether there is sufficient evidence to support a claim of a linear correlation between the two variables. (Save your work because the same data sets will be used in Section 10-2 exercises.) Sports Diameters (cm), circumferences (cm), and volumes (cm3) from balls used in different sports are listed in the table below. Is there sufficient evidence to conclude that there is a linear correlation between diameters and circumferences? Does the scatterplot confirm a linear association?arrow_forwardTesting for a Linear Correlation. In Exercises 13–28, construct a scatterplot, and find the value of the linear correlation coefficient r. Also find the P-value or the critical values of r from Table A-6. Use a significance level of α = 0.05. Determine whether there is sufficient evidence to support a claim of a linear correlation between the two variables. (Save your work because the same data sets will be used in Section 10-2 exercises.) Weighing Seals with a Camera Listed below are the overhead widths (cm) of seals measured from photographs and the weights (kg) of the seals (based on “Mass Estimation of Weddell Seals Using Techniques of Photogrammetry,” by R. Garrott of Montana State University). The purpose of the study was to determine if weights of seals could be determined from overhead photographs. Is there sufficient evidence to conclude that there is a linear correlation between overhead widths of seals from photographs and the weights of the seals?arrow_forward
- Testing for a Linear Correlation. In Exercises 13–28, construct a scatterplot, and find the value of the linear correlation coefficient r. Also find the P-value or the critical values of r from Table A-6. Use a significance level of α = 0.05. Determine whether there is sufficient evidence to support a claim of a linear correlation between the two variables. (Save your work because the same data sets will be used in Section 10-2 exercises.) Pizza and the Subway The “pizza connection” is the principle that the price of a slice of pizza in New York City is always about the same as the subway fare. Use the data listed below to determine whether there is a significant linear correlation between the cost of a slice of pizza and the subway fare.arrow_forwardTesting for a Linear Correlation. In Exercises 13–28, construct a scatterplot, and find the value of the linear correlation coefficient r. Also find the P-value or the critical values of r from Table A-6. Use a significance level of α = 0.05. Determine whether there is sufficient evidence to support a claim of a linear correlation between the two variables. (Save your work because the same data sets will be used in Section 10-2 exercises.) Tips Listed below are amounts of bills for dinner and the amounts of the tips that were left. The data were collected by students of the author. Is there sufficient evidence to conclude that there is a linear correlation between the bill amounts and the tip amounts? If everyone were to tip with the same percentage, what should be the value of r?arrow_forwardTesting for a Linear Correlation. In Exercises 13–28, construct a scatterplot, and find the value of the linear correlation coefficient r. Also find the P-value or the critical values of r from Table A-6. Use a significance level of α = 0.05. Determine whether there is sufficient evidence to support a claim of a linear correlation between the two variables. (Save your work because the same data sets will be used in Section 10-2 exercises.) Revised mpg Ratings Listed below are combined city-highway fuel economy ratings (in mi/gal) for different cars. The old ratings are based on tests used before 2008 and the new ratings are based on tests that went into effect in 2008. Is there sufficient evidence to conclude that there is a linear correlation between the old ratings and the new ratings? What do the data suggest about the old ratings?arrow_forward
- Testing for a Linear Correlation. In Exercises 13–28, construct a scatterplot, and find the value of the linear correlation coefficient r. Also find the P-value or the critical values of r from Table A-6. Use a significance level of α = 0.05. Determine whether there is sufficient evidence to support a claim of a linear correlation between the two variables. (Save your work because the same data sets will be used in Section 10-2 exercises.) Manatees Listed below are numbers of registered pleasure boats in Florida (tens of thousands) and the numbers of manatee fatalities from encounters with boats in Florida for each of several recent years. The values are from Data Set 10 “Manatee Deaths” in Appendix B. Is there sufficient evidence to conclude that there is a linear correlation between numbers of registered pleasure boats and numbers of manatee boat fatalities?arrow_forwardTesting for a Linear Correlation. In Exercises 13–28, construct a scatterplot, and find the value of the linear correlation coefficient r. Also find the P-value or the critical values of r from Table A-6. Use a significance level of α = 0.05. Determine whether there is sufficient evidence to support a claim of a linear correlation between the two variables. (Save your work because the same data sets will be used in Section 10-2 exercises.) POTUS Media periodically discuss the issue of heights of winning presidential candidates and heights of their main opponents. Listed below are those heights (cm) from several recent presidential elections (from Data Set 15 “Presidents” in Appendix B). Is there sufficient evidence to conclude that there is a linear correlation between heights of winning presidential candidates and heights of their main opponents? Should there be such a correlation?arrow_forwardSection 10.1 Question #12 Listed below are amounts of bills for dinner and the amounts of the tips that were left. Construct a scatterplot, find the value of the linear correlation coefficient r, and find the P-value of r. Determine whether there is sufficient evidence to support a claim of linear correlation between the two variables. Use a significance level of α=0.01. If everyone were to tip with the same percentage, what should be the value of r? Bill (dollars) 30.42 52.60 83.77 89.27 60.05 104.60 Tip (dollars) 5.67 5.67 9.72 9.66 9.02 15.55 The linear correlation coefficient is r= _________. (Round to three decimal places as needed.) The test statistic is t= ___________. (Round to two decimal places as needed.) The P-value is _________. (Round to three decimal places as needed.) If everyone were to tip with the same percentage, then r= _________ (Round to three decimal places as needed.)arrow_forward
- 65arrow_forwardIn a dataset, X is the independent variable, and Y is the dependent variable. Which of the following statement is correct? None of these Regression between X and Y determines the nature of the relationship between the variables. Regression between X and Y determines whether there exists any relationship between the variables. Correlation between X and Y determines the nature of the relationship between the variables.arrow_forwardThe correlation coefficient (r) measures O how many data points are shown on a scatterplot. O whether or not a scatterplot shows an interesting pattern. O whether a cause and effect relationship exists between two variables. O the strength and direction of the linear relationship between two quantitative variables.arrow_forward
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