Concept explainers
In Exercises 21–24, use technology to find the quadratic regression curve through the given points. (Round all coefficients to four decimal places.) [HINT: See Example 5.]
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Finite Mathematics and Applied Calculus (MindTap Course List)
- 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_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_forwardIn Exercises 61–64, find an equation for the level surface of the function through the given point.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. 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_forwardData were collected from a group of senior citizens, ages 65 and older, about their age and pet ownership. The results were used to calculate the model ŷ = –0.24x + 18.48, where x represents the age in years and ŷ represents the predicted number of pets owned. If a 25-year-old is predicted to have more than 12 pets, would that be a reasonable use of the model? This is reasonable because the prediction is based on someone within the original population. This is not reasonable because the prediction is based on someone outside the original population. This is reasonable because the model is based on real data. This is not reasonable because it is impossible to own more than 12 pets.arrow_forwardData were collected from a group of senior citizens, ages 65 and older, about their age and pet ownership. The results were used to calculate the model ŷ = –0.24x + 18.48, where x represents the age in years and ŷ represents the predicted number of pets owned. If a 45-year-old is predicted to have more than 7 pets, would that be a reasonable use of the model? This is not reasonable because the prediction is based on someone outside the original population. This is reasonable because the model is based on real data. This is not reasonable because it is impossible to own more than 7 pets. This is reasonable because the prediction is based on someone within the original population.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. 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?arrow_forward3.2 #11 Part 4arrow_forward
- Algebra & Trigonometry with Analytic GeometryAlgebraISBN:9781133382119Author:SwokowskiPublisher:Cengage