(b) Compute a 95% CI for the expected change in emission rate associated with a 10 MBtu/hr-ft increase in liberation rate. (Round your answers to two decimal places.) 17.27 X 17.69 x) ppm .
(b) Compute a 95% CI for the expected change in emission rate associated with a 10 MBtu/hr-ft increase in liberation rate. (Round your answers to two decimal places.) 17.27 X 17.69 x) ppm .
MATLAB: An Introduction with Applications
6th Edition
ISBN:9781119256830
Author:Amos Gilat
Publisher:Amos Gilat
Chapter1: Starting With Matlab
Section: Chapter Questions
Problem 1P
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PLEASE HELP WITH PART B) at the bottom, I keep getting incorrect. WILL THUMBS UP IF CORRECT.
![The following data is representative of that reported in an article with \( x = \) burner-area liberation rate (MBtu/hr-ft\(^2\)) and \( y = \) NO\(_x\) emission rate (ppm):
\[
\begin{array}{cccccccccccccccc}
x & 100 & 125 & 125 & 150 & 200 & 250 & 250 & 300 & 300 & 300 & 350 & 400 & 400 \\
y & 140 & 130 & 170 & 210 & 200 & 250 & 290 & 400 & 420 & 440 & 390 & 610 & 620 & 670 \\
\end{array}
\]
(a) Does the simple linear regression model specify a useful relationship between the two rates? Use the appropriate test procedure to obtain information about the \( P \)-value, and then reach a conclusion at significance level 0.01. State the appropriate null and alternative hypotheses.
- \( H_0: \, \beta_1 = 0 \)
- \( H_a: \, \beta_1 \ne 0 \) (checked)
Calculate the test statistic and determine the \( P \)-value. (Round your test statistic to two decimal places and your \( P \)-value to three decimal places.)
- \( t = 18.04 \)
- \( P \)-value = 0.000 (checked)
State the conclusion in the problem context.
- Reject \( H_0 \). There is evidence that the model is useful. (checked)
(b) Compute a 95% CI for the expected change in emission rate associated with a 10 MBtu/hr-ft\(^2\) increase in liberation rate. (Round your answers to two decimal places.)
- (17.27, 17.69) ppm (checked)](/v2/_next/image?url=https%3A%2F%2Fcontent.bartleby.com%2Fqna-images%2Fquestion%2F90e6bfeb-bff8-474c-9f48-59323e6d17cd%2F2ce9142d-1ae1-43a5-8237-0bab56322e38%2Flxkbh3i_processed.png&w=3840&q=75)
Transcribed Image Text:The following data is representative of that reported in an article with \( x = \) burner-area liberation rate (MBtu/hr-ft\(^2\)) and \( y = \) NO\(_x\) emission rate (ppm):
\[
\begin{array}{cccccccccccccccc}
x & 100 & 125 & 125 & 150 & 200 & 250 & 250 & 300 & 300 & 300 & 350 & 400 & 400 \\
y & 140 & 130 & 170 & 210 & 200 & 250 & 290 & 400 & 420 & 440 & 390 & 610 & 620 & 670 \\
\end{array}
\]
(a) Does the simple linear regression model specify a useful relationship between the two rates? Use the appropriate test procedure to obtain information about the \( P \)-value, and then reach a conclusion at significance level 0.01. State the appropriate null and alternative hypotheses.
- \( H_0: \, \beta_1 = 0 \)
- \( H_a: \, \beta_1 \ne 0 \) (checked)
Calculate the test statistic and determine the \( P \)-value. (Round your test statistic to two decimal places and your \( P \)-value to three decimal places.)
- \( t = 18.04 \)
- \( P \)-value = 0.000 (checked)
State the conclusion in the problem context.
- Reject \( H_0 \). There is evidence that the model is useful. (checked)
(b) Compute a 95% CI for the expected change in emission rate associated with a 10 MBtu/hr-ft\(^2\) increase in liberation rate. (Round your answers to two decimal places.)
- (17.27, 17.69) ppm (checked)
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