The following data is representative of that reported in the article "An Experimental Correlation of Oxides of Nitrogen Emissions from Power Boilers Based on Fleld Data,"t with x = burner-area liberation rate (MBtu/hr-ft?) and y = NO, emission rate (ppm). 100 125 125 150 150 200 200 250 250 300 300 350 400 400 150 140 180 210 190 320 280 400 430 440 390 600 610 670 The equation of the estimated regression line is y = -45.55190539 + 1.71143233x. [sSE (a) Obtain SSE for the data from the defining formula SSE = (Y, - (Round your answer to two decimal places.) Compare to the value calculated from the computational formula. (When comparing, round your value from the computational formula to two declmal places.) Rounded to two decimal places the value from the computational formula is --Select-- v the defining formula. (b) Calculate the value of total sum of squares. (Round your answer to two decimal places.) Does the simple linear regression model appear to do an effective job of explaining variation in emission rate? Justify your assertion. (Assume that a value of r2 greater than 0.85 is large enough to consider the model successful.) Since, rounded to two decimal places, r = , the simple linear regression model --Select-- to do an effective job of explaining varlatlon in emisslon rate.
The following data is representative of that reported in the article "An Experimental Correlation of Oxides of Nitrogen Emissions from Power Boilers Based on Fleld Data,"t with x = burner-area liberation rate (MBtu/hr-ft?) and y = NO, emission rate (ppm). 100 125 125 150 150 200 200 250 250 300 300 350 400 400 150 140 180 210 190 320 280 400 430 440 390 600 610 670 The equation of the estimated regression line is y = -45.55190539 + 1.71143233x. [sSE (a) Obtain SSE for the data from the defining formula SSE = (Y, - (Round your answer to two decimal places.) Compare to the value calculated from the computational formula. (When comparing, round your value from the computational formula to two declmal places.) Rounded to two decimal places the value from the computational formula is --Select-- v the defining formula. (b) Calculate the value of total sum of squares. (Round your answer to two decimal places.) Does the simple linear regression model appear to do an effective job of explaining variation in emission rate? Justify your assertion. (Assume that a value of r2 greater than 0.85 is large enough to consider the model successful.) Since, rounded to two decimal places, r = , the simple linear regression model --Select-- to do an effective job of explaining varlatlon in emisslon rate.
MATLAB: An Introduction with Applications
6th Edition
ISBN:9781119256830
Author:Amos Gilat
Publisher:Amos Gilat
Chapter1: Starting With Matlab
Section: Chapter Questions
Problem 1P
Related questions
Question
![The following data is representative of that reported in the article "An Experimental Correlation of Oxides of Nitrogen Emissions from Power Boilers Based on Field Data," with \( x = \) burner-area liberation rate (MBtu/hr-ft\(^2\)) and \( y = \) NO\(_x\) emission rate (ppm).
| \( x \) | 100 | 125 | 125 | 150 | 200 | 250 | 250 | 300 | 350 | 400 | 400 |
|--------|-----|-----|-----|-----|-----|-----|-----|-----|-----|-----|-----|
| \( y \) | 150 | 140 | 180 | 210 | 190 | 320 | 280 | 430 | 440 | 690 | 610 | 670 |
The equation of the estimated regression line is \( y = -45.55190539 + 1.71143233x \).
(a) Obtain SSE for the data from the defining formula \( \text{SSE} = \sum (y_i - \hat{y}_i)^2 \). (Round your answer to two decimal places.)
[Text box for answer]
Compare to the value calculated from the computational formula. (When comparing, round your value from the computational formula to two decimal places.)
Rounded to two decimal places the value from the computational formula is [Dropdown] the defining formula.
(b) Calculate the value of total sum of squares. (Round your answer to two decimal places.)
[Text box for answer]
Does the simple linear regression model appear to do an effective job of explaining variation in emission rate? Justify your assertion. (Assume that a value of \( r^2 \) greater than 0.85 is large enough to consider the model successful.)
Since, rounded to two decimal places, \( r^2 = \) [Text box for answer], the simple linear regression model [Dropdown] to do an effective job of explaining variation in emission rate.](/v2/_next/image?url=https%3A%2F%2Fcontent.bartleby.com%2Fqna-images%2Fquestion%2Ffea4cb18-f853-4dd5-87f1-44780e7d8dd9%2Fb17dfa05-0760-47eb-83f4-0afd6222087e%2Fi7geg9i_processed.png&w=3840&q=75)
Transcribed Image Text:The following data is representative of that reported in the article "An Experimental Correlation of Oxides of Nitrogen Emissions from Power Boilers Based on Field Data," with \( x = \) burner-area liberation rate (MBtu/hr-ft\(^2\)) and \( y = \) NO\(_x\) emission rate (ppm).
| \( x \) | 100 | 125 | 125 | 150 | 200 | 250 | 250 | 300 | 350 | 400 | 400 |
|--------|-----|-----|-----|-----|-----|-----|-----|-----|-----|-----|-----|
| \( y \) | 150 | 140 | 180 | 210 | 190 | 320 | 280 | 430 | 440 | 690 | 610 | 670 |
The equation of the estimated regression line is \( y = -45.55190539 + 1.71143233x \).
(a) Obtain SSE for the data from the defining formula \( \text{SSE} = \sum (y_i - \hat{y}_i)^2 \). (Round your answer to two decimal places.)
[Text box for answer]
Compare to the value calculated from the computational formula. (When comparing, round your value from the computational formula to two decimal places.)
Rounded to two decimal places the value from the computational formula is [Dropdown] the defining formula.
(b) Calculate the value of total sum of squares. (Round your answer to two decimal places.)
[Text box for answer]
Does the simple linear regression model appear to do an effective job of explaining variation in emission rate? Justify your assertion. (Assume that a value of \( r^2 \) greater than 0.85 is large enough to consider the model successful.)
Since, rounded to two decimal places, \( r^2 = \) [Text box for answer], the simple linear regression model [Dropdown] to do an effective job of explaining variation in emission rate.
Expert Solution
This question has been solved!
Explore an expertly crafted, step-by-step solution for a thorough understanding of key concepts.
This is a popular solution!
Trending now
This is a popular solution!
Step by step
Solved in 3 steps with 3 images
Recommended textbooks for you
MATLAB: An Introduction with Applications
Statistics
ISBN:
9781119256830
Author:
Amos Gilat
Publisher:
John Wiley & Sons Inc
Probability and Statistics for Engineering and th…
Statistics
ISBN:
9781305251809
Author:
Jay L. Devore
Publisher:
Cengage Learning
Statistics for The Behavioral Sciences (MindTap C…
Statistics
ISBN:
9781305504912
Author:
Frederick J Gravetter, Larry B. Wallnau
Publisher:
Cengage Learning
MATLAB: An Introduction with Applications
Statistics
ISBN:
9781119256830
Author:
Amos Gilat
Publisher:
John Wiley & Sons Inc
Probability and Statistics for Engineering and th…
Statistics
ISBN:
9781305251809
Author:
Jay L. Devore
Publisher:
Cengage Learning
Statistics for The Behavioral Sciences (MindTap C…
Statistics
ISBN:
9781305504912
Author:
Frederick J Gravetter, Larry B. Wallnau
Publisher:
Cengage Learning
Elementary Statistics: Picturing the World (7th E…
Statistics
ISBN:
9780134683416
Author:
Ron Larson, Betsy Farber
Publisher:
PEARSON
The Basic Practice of Statistics
Statistics
ISBN:
9781319042578
Author:
David S. Moore, William I. Notz, Michael A. Fligner
Publisher:
W. H. Freeman
Introduction to the Practice of Statistics
Statistics
ISBN:
9781319013387
Author:
David S. Moore, George P. McCabe, Bruce A. Craig
Publisher:
W. H. Freeman