The data set was obtained from 21 days of operation of a plant for the oxidation of ammonia to nitric acid. It is desired to fit a multiple linear regression model to predict Y = stack loss which is 10 times the percentage of the ingoing ammonia to the plant that escapes from the absorption column unabsorbed, as Y = Bo + B1air.flow + B2xwater.temp + B3acid.conc
The data set was obtained from 21 days of operation of a plant for the oxidation of ammonia to nitric acid. It is desired to fit a multiple linear regression model to predict Y = stack loss which is 10 times the percentage of the ingoing ammonia to the plant that escapes from the absorption column unabsorbed, as Y = Bo + B1air.flow + B2xwater.temp + B3acid.conc
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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Transcribed Image Text:The data set was obtained from 21 days of operation of
a plant for the oxidation of ammonia to nitric acid. It is
desired to fit a multiple linear regression model to
predict Y = stack loss which is 10 times the percentage
of the ingoing ammonia to the plant that escapes from
the absorption column unabsorbed, as
Y = Bo + B1Xair.flow + B2 water.temp + B3 xacid.conc
Air.Flow represents the rate of operation of the plant.
Water.Temp is the temperature of cooling water
circulated through coils in the absorption tower.
Acid.Conc is the concentration of the acid circulating,
minus 50, times 10.
This is the result of the best subsets regression.
|Summary of best subsets, variable(s): stack.loss (stt 151astackloss)
Adjusted R square and standardized
regression coefficients for each submodel
Adjusted
R square
0.898623
No. of
Effects
Air. Flow
Water.Temp
Acid.Conc.
Subset No.
1
2 0.604950
0.402523
This is the result of the forward stepwise regression.
Degr. of
Freedom
P to
enter
0.000000
Effect
status
Entered
Steps
F to
P to
Fto
remove
remove
enter
Effect
Air.Flow
Water. Temp
Acid.Conc
Air.Flow
Water. Temp
Acid.Conc.
Step Number 1
104.2013
62.3732
0.000000
Out
3.6154
0.072523
Out
In
Entered
Step Number 2
104 2013
0.000000
0.002419
0.455788
1
12.4250
0.5810
Out
In
Step Number 3
1.
28.0642 0.000049
Air.Flow
Water.Temp
Açid.Conc.
1
12.4250
0.002419
In
1
0.9473
0.344046
Out
Which of the following statements is/are true?
I. The optimal model by best subsets regression and
forward stepwise regression is the same.
II. The total number of linear regression models that can
be made for the data set is 15.
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