A study of a high-pressure inlet fogging method for a gas turbine engine analyzed a complete second-order model for y, heat rate (kilojoules per kilowatt per hour) of a gas turbine as a function of two quantitative variables • X1 , cycle speed (revolutions per minute) • x2, cycle pressure ratio and a qualitative predictor, engine type, at three levels (traditional, advanced, and aeroderivative). We define two dummy variables S1 if advanced X3 = 0if not 1 if aeroderivative and X4 = not There are 67 observations in the dataset. We conduct a global F-test for overall model adequacy at a level of significance 5%. 1. Numerator degrees of freedom 2. Denominator degrees of freedom 3. If F-value equals to 30.52, then we (reject or fail to reject) the null hypothesis at 5%. There is (sufficient or insufficient) that the complete second-order model is overall useful.
A study of a high-pressure inlet fogging method for a gas turbine engine analyzed a complete second-order model for y, heat rate (kilojoules per kilowatt per hour) of a gas turbine as a function of two quantitative variables • X1 , cycle speed (revolutions per minute) • x2, cycle pressure ratio and a qualitative predictor, engine type, at three levels (traditional, advanced, and aeroderivative). We define two dummy variables S1 if advanced X3 = 0if not 1 if aeroderivative and X4 = not There are 67 observations in the dataset. We conduct a global F-test for overall model adequacy at a level of significance 5%. 1. Numerator degrees of freedom 2. Denominator degrees of freedom 3. If F-value equals to 30.52, then we (reject or fail to reject) the null hypothesis at 5%. There is (sufficient or insufficient) that the complete second-order model is overall useful.
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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![A study of a high-pressure inlet fogging method for a gas turbine engine analyzed a complete
second-order model for y, heat rate (kilojoules per kilowatt per hour) of a gas turbine as a function
of two quantitative variables
• x1 , cycle speed (revolutions per minute)
• x2 , cycle pressure ratio
and a qualitative predictor, engine type, at three levels (traditional, advanced, and aeroderivative).
We define two dummy variables
(1 if advanced
X3 =
0 if not
{o
1
and X4 =
ここ
if aeroderivative
0if not
There are 67 observations in the dataset. We conduct a global F-test for overall model adequacy at a
level of significance 5%.
1. Numerator degrees of freedom
2. Denominator degrees of freedom
3. If F-value equals to 30.52, then we
(reject or fail to reject) the null
hypothesis at 5%. There is
(sufficient or insufficient) that the complete
second-order model is overall useful.](/v2/_next/image?url=https%3A%2F%2Fcontent.bartleby.com%2Fqna-images%2Fquestion%2Fe8b2986c-138a-4e9c-92a6-11213a295c30%2F1f1a98e0-5d96-47fe-b01d-357909c996ab%2Fhdn9fb_processed.jpeg&w=3840&q=75)
Transcribed Image Text:A study of a high-pressure inlet fogging method for a gas turbine engine analyzed a complete
second-order model for y, heat rate (kilojoules per kilowatt per hour) of a gas turbine as a function
of two quantitative variables
• x1 , cycle speed (revolutions per minute)
• x2 , cycle pressure ratio
and a qualitative predictor, engine type, at three levels (traditional, advanced, and aeroderivative).
We define two dummy variables
(1 if advanced
X3 =
0 if not
{o
1
and X4 =
ここ
if aeroderivative
0if not
There are 67 observations in the dataset. We conduct a global F-test for overall model adequacy at a
level of significance 5%.
1. Numerator degrees of freedom
2. Denominator degrees of freedom
3. If F-value equals to 30.52, then we
(reject or fail to reject) the null
hypothesis at 5%. There is
(sufficient or insufficient) that the complete
second-order model is overall useful.
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