Elementary Statistics (13th Edition)
13th Edition
ISBN: 9780134462455
Author: Mario F. Triola
Publisher: PEARSON
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Chapter 10.2, Problem 7BSC
Making Predictions. In Exercises 5–8, let the predictor variable x be the first variable given. Use the given data to find the regression equation and the best predicted value of the response variable. Be sure to follow the prediction procedure summarized in Figure 10-5 on page 493. Use a 0.05 significance level.
7. Height and Weight Heights (cm) and weights (kg) are measured for 100 randomly selected adult males (from Data Set 1 “Body Data” in Appendix B). The 100 paired measurements yield
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Making Predictions. In Exercises 5–8, let the predictor variable x be the first variable given. Use the given data to find the regression equation and the best predicted value of the response variable. Be sure to follow the prediction procedure summarized in Figure 10-5 on page 493. Use a 0.05 significance level.
Bear Measurements Head widths (in.) and weights (lb) were measured for 20 randomly selected bears (from Data Set 9 “Bear Measurements” in Appendix B). The 20 pairs of measurements yield x = 6.9 in., ȳ = 214.3 lb, r = 0.879, P -value = 0.000, and ŷ = −212 + 61.9x. Find the best predicted value of ŷ (weight) given a bear with a head width of 6.5 in.
Regression and Predictions. Exercises 13–28 use the same data sets as Exercises 13–28 in Section 10-1. In each case, find the regression equation, letting the first variable be the predictor (x) variable. Find the indicated predicted value by following the prediction procedure summarized in Figure 10-5 on page 493.
Tips Using the bill/tip data, find the best predicted tip amount for a dinner bill of $100. What tipping rule does the regression equation suggest?
Regression and Predictions. Exercises 13–28 use the same data sets as Exercises 13–28 in Section 10-1. In each case, find the regression equation, letting the first variable be the predictor (x) variable. Find the indicated predicted value by following the prediction procedure summarized in Figure 10-5 on page 493.
Internet and Nobel Laureates Find the best predicted Nobel Laureate rate for Japan, which has 79.1 Internet users per 100 people. How does it compare to Japan’s Nobel Laureate rate of 1.5 per 10 million people?
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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- Regression and Predictions. Exercises 13–28 use the same data sets as Exercises 13–28 in Section 10-1. In each case, find the regression equation, letting the first variable be the predictor (x) variable. Find the indicated predicted value by following the prediction procedure summarized in Figure 10-5 on page 493. CPI and the Subway Use the CPI/subway fare data from the preceding exercise and find the best predicted subway fare for a time when the CPI reaches 500. What is wrong with this prediction?arrow_forwardInterpreting a Computer Display. In Exercises 5–8, we want to consider the correlation between heights of fathers and mothers and the heights of their sons. Refer to the StatCrunch display and answer the given questions or identify the indicated items. The display is based on Data Set 5 “Family Heights” in Appendix B. Height of Son A son will be bom to a father who is 70 in. tall and a mother who is 60 in. tall. Use the multiple regression equation to predict the height of the son. Is the result likely to be a good predicted value? Why or why not?arrow_forwardCity 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). A Honda Civic weighs 2740 lb, it has an engine displacement of 1.8 L, and its highway fuel consumption is 36 mi/gal. What is the best predicted value of the city fuel consumption? Is that predicted value likely to be a good estimate? Is that predicted value likely to be very accurate?arrow_forward
- 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). Which regression equation is best for predicting city fuel consumption? Why?arrow_forwardCity 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). If exactly two predictor (x) variables are to be used to predict the city fuel consumption, which two variables should be chosen? Why?arrow_forwardIn the regression model ŷ = a + bx, a and b are the: omitted variables O sample statistics O random variables O population parametersarrow_forward
- 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.arrow_forwarda. Estimate the regression line and also write the prediction equation. y = 83.4578-5.8795 x y = 5.8795 + 83.4578 x ŷ ŷ= = -5.8795 + 83.4578 x = 83.4578 + 5.8795 xarrow_forward3. Regression analysis breaks scores on the DV into... (explain and give equations)arrow_forward
- 33)arrow_forwarda. Draw a scatter diagram for the data. b. Draw a regression line of y on x. c. Determine the equation of the line of best fit.arrow_forwarda) Determine sum of squares of error (SSE) and correlation coefficient (R?) for the model. b) Estimate the parameters of reaction model with 95% confidence limits. c) Evaluate the fit of the model equation you obtained to your data. d) Estimate concentration of flavor compound after 17 days of storage by using the best model. Time Concentration (d) (mg/L) 561.00 569.67 3. 252.11 258.40 7. 107.95 7. 113.22 10 47.77 10 50.83 15 23.80 15 22.95 23 9.35 23 10.20arrow_forward
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