ELEM STATISTICS PKG W/STATLAB SPSCC>CI
2nd Edition
ISBN: 9781269391757
Author: Triola
Publisher: PEARSON C
expand_more
expand_more
format_list_bulleted
Concept explainers
Videos
Textbook Question
Chapter 10.3, Problem 14BSC
Regression and Predictions. Exercises 13-28 use the same data sets as Exercises 13-28 in Section 10-2. 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.
14. PSAT and SAT Scores One subject not included in the given table had a PSAT score of 229- Find the best predicted SAT score for this student. Is the result close to the reported value of 2400? Given that the data are from volunteered responses, are the results valid?
| PSAT | 183 | 207 | 167 | 206 | 197 | 142 | 193 | 176 |
| SAT | 2200 | 2040 | 1890 | 2380 | 2290 | 2070 | 2370 | 1980 |
Expert Solution & Answer
Want to see the full answer?
Check out a sample textbook solution
Students have asked these similar questions
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.
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?
Chapter 10 Solutions
ELEM STATISTICS PKG W/STATLAB SPSCC>CI
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...
Ch. 10.2 - Outlier Refer in the accompanying...Ch. 10.2 - Clusters Refer to the following Minitab-generated...Ch. 10.2 - Testing for a Linear Correlation. In Exercises...Ch. 10.2 - Prob. 14BSCCh. 10.2 - Testing for a Linear Correlation. In Exercises...Ch. 10.2 - Testing for a Linear Correlation. In Exercises...Ch. 10.2 - Testing for a Linear Correlation. In Exercises...Ch. 10.2 - Testing for a Linear Correlation. In Exercises...Ch. 10.2 - Prob. 19BSCCh. 10.2 - Prob. 20BSCCh. 10.2 - Testing for a Linear Correlation. In Exercises...Ch. 10.2 - Testing for a Linear Correlation. In Exercises...Ch. 10.2 - Prob. 23BSCCh. 10.2 - Prob. 24BSCCh. 10.2 - Testing for a Linear Correlation. In Exercises...Ch. 10.2 - Prob. 26BSCCh. 10.2 - Testing for a Linear Correlation. In Exercises...Ch. 10.2 - Testing for a Linear Correlation. In Exercises...Ch. 10.2 - Large Data Sets. In Exercises 29-32, use the data...Ch. 10.2 - Large Data Sets. 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. Exercises 13-28 use...Ch. 10.3 - Regression and Predictions. Exercises 13-28 use...Ch. 10.3 - Regression and Predictions. Exercises 13-28 use...Ch. 10.3 - Regression and Predictions. Exercises 13-28 use...Ch. 10.3 - Regression and Predictions. Exercises 13-28 use...Ch. 10.3 - Regression and Predictions. Exercises 13-28 use...Ch. 10.3 - Regression and Predictions. Exercises 13-28 use...Ch. 10.3 - Regression and Predictions. Exercises 13-28 use...Ch. 10.3 - Regression and Predictions. Exercises 13-28 use...Ch. 10.3 - Regression and Predictions. Exercises 13-28 use...Ch. 10.3 - Regression and Predictions. Exercises 13-28 use...Ch. 10.3 - Regression and Predictions. Exercises 13-28 use...Ch. 10.3 - Regression and Predictions. Exercises 13-28 use...Ch. 10.3 - Regression and Predictions. Exercises 1328 use the...Ch. 10.3 - Regression and Predictions. Exercises 1328 use the...Ch. 10.3 - Regression and Predictions. Exercises 1328 use the...Ch. 10.3 - Large Data Sets. 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. In Exercises 5-16,...Ch. 10.6 - Prob. 11BSCCh. 10.6 - Prob. 12BSCCh. 10.6 - Prob. 13BSCCh. 10.6 - Prob. 14BSCCh. 10.6 - Prob. 15BSCCh. 10.6 - Prob. 16BSCCh. 10.6 - Prob. 18BBCh. 10 - The exercises arc based on the following sample...Ch. 10 - Prob. 2CQQCh. 10 - Prob. 3CQQCh. 10 - The exercises are based on the following sample...Ch. 10 - The exercises are based on the following sample...Ch. 10 - Prob. 6CQQCh. 10 - Prob. 7CQQCh. 10 - Prob. 8CQQCh. 10 - Prob. 9CQQCh. 10 - Prob. 10CQQCh. 10 - Old Faithful The table below lists measurements...Ch. 10 - Prob. 2RECh. 10 - Prob. 3RECh. 10 - Prob. 4RECh. 10 - Prob. 5RECh. 10 - Prob. 1CRECh. 10 - Prob. 2CRECh. 10 - Prob. 3CRECh. 10 - Prob. 4CRECh. 10 - Effectiveness of Diet. Listed below are weights...Ch. 10 - Prob. 6CRECh. 10 - Prob. 7CRECh. 10 - Effectiveness of Diet. Listed below are weights...Ch. 10 - Prob. 9CRECh. 10 - Prob. 10CRECh. 10 - Critical Thinking: Is replication validation? The...Ch. 10 - Prob. 2FDDCh. 10 - Prob. 3FDD
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
- Olympic Pole Vault The graph in Figure 7 indicates that in recent years the winning Olympic men’s pole vault height has fallen below the value predicted by the regression line in Example 2. This might have occurred because when the pole vault was a new event there was much room for improvement in vaulters’ performances, whereas now even the best training can produce only incremental advances. Let’s see whether concentrating on more recent results gives a better predictor of future records. (a) Use the data in Table 2 (page 176) to complete the table of winning pole vault heights shown in the margin. (Note that we are using x=0 to correspond to the year 1972, where this restricted data set begins.) (b) Find the regression line for the data in part ‚(a). (c) Plot the data and the regression line on the same axes. Does the regression line seem to provide a good model for the data? (d) What does the regression line predict as the winning pole vault height for the 2012 Olympics? Compare this predicted value to the actual 2012 winning height of 5.97 m, as described on page 177. Has this new regression line provided a better prediction than the line in Example 2?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_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. Oscars Using the listed actress/actor ages, find the best predicted age of the Best Actor given that the age of the Best Actress is 54 years. Is the result reasonably close to the Best Actor’s (Eddie Redmayne) actual age of 33 years, which happened in 2015, when the Best Actress was Julianne Moore, who was 54 years of age?arrow_forward
- 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?arrow_forwardChapter 9, Section 1, Exercise 006 Computer output for fitting a simple linear model is given below. State the value of the sample slope for this model and give the null and alternative hypotheses for testing if the slope in the population is different from zero. Identify the p-value and use it (and a 5% significance level) to make a clear conclusion about the effectiveness of the model.The regression equation is Y=81.0-0.0155X. Predictor Coef SE Coef T P Constant 80.96 11.62 6.97 0.000 X -0.01546 0.01288 -1.20 0.245arrow_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_forward
- 3. Life ExpectancyWe have considered a regression equation to predict life expectancy from percent of government expenditure on health care, using data for a sample of 50 countries in SampCountries. Using technology and this dataset, find a 95% prediction interval for each of the following situations. (a) A country which puts only 3% of its expenditure into health care. Round your answers to one decimal place. (b) A country which puts 10% of its expenditure into health care. Round your answers to two decimal places. (c) A country which puts 50% of its expenditure into health care. Round your answers to two decimal places. Country Health LifeExpectancy Iceland 15.76 83.1 Kazakhstan 10.90 70.5 Lesotho 14.48 49.3 Uzbekistan 9.68 68.2 Peru 14.75 74.8 Iraq 5.99 69.5 Nicaragua 20.89 74.8 Zambia 12.57 58.1 Guinea-Bissau 7.79 54.3 Romania 12.17 74.5 United States 20.71 78.8 Sierra Leone 11.41 45.6 Malta 13.29 80.7 Luxembourg 13.64 81.8 Micronesia, Fed. Sts.…arrow_forwardGiven a regression equation ?) = 2.35 + 6.82x, with n = 18 and a correlationcoefficient, r = 0.42, conduct a hypothesis test to determine if the regressionrelationship between x and y is statistically significant at the 2% level ofsignificance. What conclusion can be drawn from the hypothesis test?arrow_forwardCinema HD an online movie streaming service that offers a wide variety of award-winning TV shows, movies, animes, and documentaries, would like to determine the mathematical trend of memberships in order to project future needs. Year 2013 2014 2015 2016 2017 2018 2019 2020 2021 Membership 17 16 16 21 20 20 23 25 24 Use the following time series data, to develop a regression equation relating memberships to time. Forecast 2023 membership Assuming the COVID-19 pandemic comes to an end in 2021, in your opinion, how will this affect membership? Why? How will this affect your prediction? What are the issues associated with qualitative forecasting, and how are these overcome? Provide an example of qualitative forecasting and explain the shortcomings.arrow_forward
- The regression model Yi=−303.8+1.5949X1i−0.0699X2i predicts standby hours based on total staff present, X1i, and remote hours, X2i, for week i. The data from which the model was constructed are provided. b. If appropriate, perform the Durbin-Watson test, using α=0.05. Determine the Durbin-Watson statistic.arrow_forwardxi 2 6 9 13 20 yi 7 18 9 26 23 The estimated regression equation for these data is ŷ = 7.6+0.9x. What percentage of the total sum of squares can be accounted for by the estimated regression equation? What is the value of the sample correlation coefficient?arrow_forwardIn a statistics course, a linear regression equation was computed to predict the final exam score from the score on the midterm exam. The equation of the least‑squares regression line was ?̂ =10+0.9?, where ?y represents the final exam score and ?x is the midterm exam score. Suppose Joe scores an 80 on the midterm exam. What would be the predicted value of his score on the final exam?arrow_forward
arrow_back_ios
SEE MORE QUESTIONS
arrow_forward_ios
Recommended textbooks for you
College AlgebraAlgebraISBN:9781305115545Author:James Stewart, Lothar Redlin, Saleem WatsonPublisher:Cengage Learning
College Algebra
Algebra
ISBN:9781305115545
Author:James Stewart, Lothar Redlin, Saleem Watson
Publisher:Cengage Learning
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