Elementary Statistics with Student Access Kit
12th Edition
ISBN: 9780321869470
Author: Mario F. Triola
Publisher: PEARSON
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Chapter 10.3, Problem 27BSC
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, bind the indicated predicted value by following the prediction procedure summarized in Figure 10-5 on page 493.
| Baseball | basketball | Golf | Soccer | Tennis | Ping-Pong | Volleyball | Softball | |
| Diameter | 7.4 | 23.9 | 4.3 | 21.8 | 7.0 | 4.0 | 20.9 | 9.7 |
| Circumference | 23.2 | 75.1 | 13.5 | 60.5 | 22.0 | 12.6 | 65.7 | 30.5 |
| Volume | 212.2 | 7148.1 | 41.6 | 5424.6 | 179.6 | 33.5 | 4760.1 | 477.9 |
27. Sports Using the diameter/circumference data, find the best predicted circumference of a marble with a diameter of 1.50 cm. How does the result compare to the actual circumference of 4.7 cm?
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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.
Manatees Use the listed boat/manatee data. In a year not included in the data below, there were 970,000 registered pleasure boats in Florida. Find the best predicted number of manatee fatalities resulting from encounters with boats. Is the result reasonably close to 79, which was the actual number of manatee fatalities?
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?
Altman Z Score
2018
2019
2020
BHP
0.80
0.71
0.63
FMG
1.12
1.26
1.38
RIO
1.36
1.34
1.34
Comment on the findings of each company and is it useful in predicting financial failure
Chapter 10 Solutions
Elementary Statistics with Student Access Kit
Ch. 10.2 - Notation For each of several randomly selected...Ch. 10.2 - Physics Experiment A physics experiment consists...Ch. 10.2 - Cause of High Blood Pressure Some studies have...Ch. 10.2 - Notation What is the difference between the...Ch. 10.2 - Interpreting r. In Exercises 5-8, use a...Ch. 10.2 - Interpreting r. In Exercises 5-8, use a...Ch. 10.2 - Interpreting r. In Exercises 5-8, use a...Ch. 10.2 - Cereal Killers The amounts of sugar (grams of...Ch. 10.2 - Explore! Exercises 9 and 10 provide two data sets...Ch. 10.2 - Explore! Exercises 9 and 10 provide two data sets...
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In Exercises 29-32, use the data...Ch. 10.2 - Appendix B Data Sets. In Exercises 29-34, use the...Ch. 10.2 - Large Data Sets. In Exercises 29-32, use the data...Ch. 10.2 - Transformed Data In addition to testing for a...Ch. 10.2 - Prob. 34BBCh. 10.3 - Notation and Terminology If we use the paired...Ch. 10.3 - Best-Fit Line In what sense is the regression line...Ch. 10.3 - Prob. 3BSCCh. 10.3 - Notation What is the difference between the...Ch. 10.3 - Making Predictions. In Exercises 5-8, let the...Ch. 10.3 - Making Predictions. In Exercises 5-8, let the...Ch. 10.3 - Making Predictions. In Exercises 5-8, let the...Ch. 10.3 - Making Predictions. In Exercises 5-8, let the...Ch. 10.3 - Finding the Equation of the Regression Line. In...Ch. 10.3 - Finding the Equation of the Regression Line. In...Ch. 10.3 - Effects of an Outlier Refer to the Mini...Ch. 10.3 - Effects of Clusters Refer to the Minitab-generated...Ch. 10.3 - Regression and Predictions. 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Exercises 2932 use the same...Ch. 10.3 - Large Data Sets. Exercises 2932 use the same...Ch. 10.3 - Prob. 31BSCCh. 10.3 - Large Data Sets. Exercises 29-32 use the same...Ch. 10.3 - Prob. 33BBCh. 10.3 - Prob. 34BBCh. 10.4 - Prob. 1BSCCh. 10.4 - Prediction Interval Using the heights and weights...Ch. 10.4 - Prob. 3BSCCh. 10.4 - Prob. 4BSCCh. 10.4 - Interpreting the Coefficient of Determination. In...Ch. 10.4 - Interpreting the Coefficient of Determination. In...Ch. 10.4 - Interpreting the Coefficient of Determination. In...Ch. 10.4 - Interpreting the Coefficient of Determination. In...Ch. 10.4 - Prob. 9BSCCh. 10.4 - Prob. 10BSCCh. 10.4 - Prob. 11BSCCh. 10.4 - Prob. 12BSCCh. 10.4 - Prob. 13BSCCh. 10.4 - Prob. 14BSCCh. 10.4 - Prob. 15BSCCh. 10.4 - Prob. 16BSCCh. 10.4 - Variation and Prediction Intervals. In Exercises...Ch. 10.4 - Prob. 18BSCCh. 10.4 - Prob. 19BSCCh. 10.4 - Prob. 20BSCCh. 10.4 - Confidence Intervals for 0 and 1 Confidence...Ch. 10.4 - Confidence Interval for Mean Predicted Value...Ch. 10.5 - Prob. 1BSCCh. 10.5 - Best Multiple Regression Equation For the...Ch. 10.5 - Adjusted Coefficient of Determination For Exercise...Ch. 10.5 - Interpreting R2 For the multiple regression...Ch. 10.5 - Prob. 5BSCCh. 10.5 - Prob. 6BSCCh. 10.5 - Prob. 7BSCCh. 10.5 - Prob. 8BSCCh. 10.5 - Prob. 9BSCCh. 10.5 - Prob. 10BSCCh. 10.5 - Prob. 11BSCCh. 10.5 - City Fuel Consumption: Finding the Best Multiple...Ch. 10.5 - Prob. 13BSCCh. 10.5 - Prob. 14BSCCh. 10.5 - Appendix B Data Sets. In Exercises 13-16, refer to...Ch. 10.5 - Appendix B Data Sets. In Exercises 13-16, refer to...Ch. 10.5 - Prob. 17BBCh. 10.5 - Prob. 18BBCh. 10.5 - Dummy Variable Refer to Data Set 9 Bear...Ch. 10.6 - Prob. 1BSCCh. 10.6 - Prob. 2BSCCh. 10.6 - Super Bowl and R2 Let x represent years coded as...Ch. 10.6 - Prob. 4BSCCh. 10.6 - Prob. 5BSCCh. 10.6 - Finding the Best Model. In Exercises 5-16,...Ch. 10.6 - Prob. 7BSCCh. 10.6 - Prob. 8BSCCh. 10.6 - Finding the Best Model. In Exercises 5-16,...Ch. 10.6 - Finding the Best Model. 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- If the general linear regression model is given by the equation: y = a + b?; considering the informationobtained in Figure 2 above, compute the value of a.arrow_forwardgiven the information below: Row Education Income in in Years 2015 Dollars 1 7 22587 2 10 28305 3 12 40196 4 13 49483 5 14 54483 6 16 78073 7 18 99540 8 19 155646 9 21 125310 1. Estimate the regression equation Income = a + b(Education). 2. What is the predicted increase in Income for a one-year increase in Education? 3. What do you predict Income to be for a person who has 17 years of education? 4. How much of the variation in Income is explained (or accounted for) by Education?arrow_forwardRegression 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. Crickets and Temperature Find the best predicted temperature at a time when a cricket chirps 3000 times in 1 minute. What is wrong with this predicted temperature?arrow_forward
- Section 10.2 Question #5 Use the given data to find the equation of the regression line. Examine the scatterplot and identify a characteristic of the data that is ignored by the regression line. x 7 10 8 9 12 14 13 5 11 6 4 y 8.11 10.67 9.27 10.12 10.86 9.82 10.49 4.89 10.91 6.66 2.82 y= ____________+ _____________x (Round to two decimal places as needed.)arrow_forwardAll of the following models would be appropriate for data comprised of randomness and trend except: a. Holt’s exponential smoothing b. Holt-winter’s exponential smoothing c. Average change model d. Linear trend regression (time series decomposition) e. All of the above would be appropriatearrow_forwardConsider the following model:? = ?? + ?,known as the Classical Linear Regression Model (CLRM), where y is the dependent variable, X is the set of independent variables, ? is the vector of parameters to be estimated and ? is the error term. Present and discuss the R2 and the adjusted R2. Discuss pros and cons of each of the two statistics.arrow_forward
- The quadratic regression equation shown below is for a sample of n=22. Determine the critical value(s).arrow_forwardSection 10.2 Question #8 Find the regression equation, letting the first variable be the predictor (x) variable. Using the listed lemon/crash data, where lemon imports are in metric tons and the fatality rates are per 100,000 people, find the best predicted crash fatality rate for a year in which there are 450metric tons of lemon imports. Is the prediction worthwhile? Lemon Imports 226 270 364 488 525 Crash Fatality Rate 16.1 15.9 15.6 15.5 15.1 Find the equation of the regression line. y= ___________+( ____________)x (Round the y-intercept to three decimal places as needed. Round the slope to four decimal places as needed.) The best predicted crash fatality rate for a year in which there are 450 metric tons of lemon imports is _________ fatalities per 100,000 population. (Round to one decimal place as needed.)arrow_forward2.state each of the five assumptions of the classical regression model (OLS) and give an intuitive explanation of the meaning and need for each of themarrow_forward
- 2. Given the following sets of information, find the linear least squares regression and the correlation coefficient.arrow_forwardChapter 10 Use the (x, y) data. x 2 4 3 6 7 9 5 12 y 25 22 24 20 17 19 12 11 Construct a scatter plot Test for correlation. Assume all requirements have been met. Is this a left, right, or two tailed test? Find the P-value? Will the null hypothesis be rejected? Write the regression equation. Round to 1 decimal place Use the regression equation to predict y when x = 5arrow_forwardConsider the linear regression model ??=?0+?1??+?? and assume that ?(??|??)=4 for each ?=1,...,?. Which one of the following is true about the interpretation of ?0? a. ?0=?(??|??=0) b. ?0 is the estimated average change in the value of ?? when we change the value of ?? c. ?0 is the predicted value of ?? when ??=0 d. ?0=?(??|??=0)−4arrow_forward
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