The following data is representative of that reported in an article on nitrogen emissions, with x burner area liberation rate (MBtu/hr-ft2) and y NO, emission rate (ppm) x100 125 125 150 150 200 200 250 250 300 300 350 400 400 160 140 190 210 200 320 280 400 440 430 400 600 600 660 (a) Assuming that the simple linear regression model is valid, obtain the least squares estimate of the true regression line. (Round all numerical values to four decimal places.) (b) What is the estimate of expected NO, emission rate when burner area liberation rate equals 240? (Round your answer to two decimal places.) ppm (c) Estimate the amount by which you expect NO, emission rate to change when burner area liberation rate is decreased by 60. (Round your answer to two decimal places.) ppm (d) Would you use the estimated regression line to predict emission rate for a liberation rate of 500? Why or why not? OYes, the data is perfectly linear, thus lending to accurate predictions. O Yes, this value is between two existing values. No, this value is too far away from the known values for useful extrapolation. No, the data near this point deviates from the overall regression model.
The following data is representative of that reported in an article on nitrogen emissions, with x burner area liberation rate (MBtu/hr-ft2) and y NO, emission rate (ppm) x100 125 125 150 150 200 200 250 250 300 300 350 400 400 160 140 190 210 200 320 280 400 440 430 400 600 600 660 (a) Assuming that the simple linear regression model is valid, obtain the least squares estimate of the true regression line. (Round all numerical values to four decimal places.) (b) What is the estimate of expected NO, emission rate when burner area liberation rate equals 240? (Round your answer to two decimal places.) ppm (c) Estimate the amount by which you expect NO, emission rate to change when burner area liberation rate is decreased by 60. (Round your answer to two decimal places.) ppm (d) Would you use the estimated regression line to predict emission rate for a liberation rate of 500? Why or why not? OYes, the data is perfectly linear, thus lending to accurate predictions. O Yes, this value is between two existing values. No, this value is too far away from the known values for useful extrapolation. No, the data near this point deviates from the overall regression model.
College Algebra
7th Edition
ISBN:9781305115545
Author:James Stewart, Lothar Redlin, Saleem Watson
Publisher:James Stewart, Lothar Redlin, Saleem Watson
Chapter1: Equations And Graphs
Section: Chapter Questions
Problem 10T: Olympic Pole Vault The graph in Figure 7 indicates that in recent years the winning Olympic men’s...
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One factor in the development of tennis elbow, a malady that strikes fear in the hearts of all serious tennis players, is the impact-induced vibration of the racket-and-arm system at ball contact. It is well known that the likelihood of getting tennis elbow depends on various properties of the racket used. Consider the
Transcribed Image Text:The following data is representative of that reported in an article on nitrogen emissions, with x = burner area liberation rate (MBtu/hr-ft2) and y = NOx emission rate (ppm):
100 125 125 150 150 200 200 250 250 300 300 350 400 400
y 160 140 190 210 200 320 280 400 440 430 400 600 600 660
(a) Assuming that the simple linear regression model is valid, obtain the least squares estimate of the true regression line. (Round all numerical values to four decimal places.)
(b) What is the estimate of expected NOx emission rate when burner area liberation rate equals 240? (Round your answer to two decimal places.)
ppm
(c) Estimate the amount by which you expect NOx emission rate to change when burner area liberation rate is decreased by 60. (Round your answer to two decimal places.)
ppm
(d) Would you use the estimated regression line to predict emission rate for a liberation rate of 500? Why or why not?
O Yes, the data is perfectly linear, thus lending to accurate predictions.
O Yes, this value is between two existing values.
O No, this value is too far away from the known values for useful extrapolation.
O No, the data near this point deviates from the overall regression model.
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