**Data for Nitrogen Emissions Study**This exercise is based on data representative of that reported in an article on nitrogen emissions, where \( x = \) burner area liberation rate (MBtu/hr-ft\(^2\)) and \( y = \) NO\(_X\) emission rate (ppm):\[\begin{array}{c|ccccccccccc}x & 100 & 125 & 125 & 150 & 150 & 200 & 200 & 250 & 250 & 300 & 300 & 350 & 400 & 400 \\y & 150 & 150 & 190 & 210 & 190 & 330 & 290 & 410 & 430 & 430 & 390 & 610 & 610 & 670 \\\end{array}\]**Use of SALT Tool****(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.)Incorrect answer given:\[ y = -39.251 + 1.7059 \]*Error Message:* Check the degree of your polynomial.**(b)** What is the estimate of expected NO\(_X\) emission rate when the burner area liberation rate equals 245? (Round your answer to two decimal places.)Incorrect Answer: 361.63 ppm**(c)** Estimate the amount by which you expect the NO\(_X\) emission rate to change when the burner area liberation rate is decreased by 60. (Round your answer to two decimal places.)Incorrect Answer: 28.98 ppm**(d)** Would you use the estimated regression line to predict emission rate for a liberation rate of 500? Why or why not?Selected Answer:- No, this value is too far away from the known values for useful extrapolation.*Feedback Confirmation:*The correct option was selected, suggesting that extrapolation beyond the range of given data should be approached with caution.

(b) The values given in the question are as follows : Let, x = burner area liberation and y =NOx…

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): X 100 125 125 150 150 200 200 250 250 300 300 350 400 400 y 150 150 190 210 190 330 290 410 430 430 390 610 610 670 USE SALT (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.) y = -39.251 + 1.7059 X Check the degree of your polynomial. (b) What is the estimate of expected NOx emission rate when burner area liberation rate equals 245? (Round your answer to two decimal places.) 361.63 x 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.) 28.98 x ppm (d) Would you use the estimated regression line to predict emission rate for a liberation rate of 500? Why or why not? 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. No, the data near this point deviates from the overall regression model.

10th Edition

ISBN:9780134753119

Author:Sheldon Ross

Publisher:Sheldon Ross

Chapter1: Combinatorial Analysis

Section: Chapter Questions

Problem 1.1P: a. How many different 7-place license plates are possible if the first 2 places are for letters and...