Which statement(s) are incorrect for the Regression Analysis shown here? (Note: There are 2 correct answers). Regression Analysis: Turbine Output versus Air-Fuel Ratio, \% steam, ... The Regression Equation it Turbine Output =16.5+3.21 Air-Fuel Ratio +0.386% methane + 0.0166 Steam Exit Temp Predictor Coef SE Coef T P Constant 16.488 2.918 5.65 0.000 Air-Fuel Ratio 3.2148 9.2377 13.52 0.000 % methane 0.38637 0.07278 5.31 0.000 Steam Exit Temp 0.016576 0.004273 3.88 0.004 S=0.508616 {R}-{Sq}=98.6 \% {R}-{Sq}({adj}])=98.2 % Arialysis of Variance Source DF SS MS F P Regression 3 170.003 56.668 219.06 0.000 Residual Error 9 2.326 0.259 Total 12 172.331 Source. DF Seq SS Air-Fuel Ratio 1 159.048 % Methane 1 7.062 Steam Exit.Temp 1 3.892

The air-fuel ratio explains most of the TurbineOutput variation

The Regression explains over 98% of the process variation

This Multiple Linear Regression has three statistically significant independent variables

If the air-fuel ratio increases by 1, the TurbineOutput more than triples

The SteamExitTemp explains the most variation of the TurbineOutput

Six Sigma Lean Black Belt Certification Questions Part 1

Question : 21 of 40

Marks: +1, -0

Which statement(s) are incorrect for the Regression Analysis shown here? (Note: There are 2 correct answers).
Regression Analysis: Turbine Output versus Air-Fuel Ratio, \% steam, ...
The Regression Equation it
Turbine Output

=16.5+3.21

Air-Fuel Ratio

+0.386%

methane

+ 0.0166

Steam Exit Temp

Predictor	Coef	SE Coef	T	P
Constant	$16.488$	$2.918$	$5.65$	0.000
Air-Fuel Ratio	$3.2148$	$9.2377$	$13.52$	0.000
% methane	$0.38637$	$0.07278$	$5.31$	0.000
Steam Exit Temp	$0.016576$	$0.004273$	$3.88$	0.004

S=0.508616

{R}-{Sq}=98.6 \%

{R}-{Sq}({adj}])=98.2 %

Arialysis of Variance

Source	DF	SS	MS	F	P
Regression	3	170.003	56.668	219.06	0.000
Residual Error	9	2.326	0.259
Total	12	172.331

Source.	DF	Seq SS
Air-Fuel Ratio	1	159.048
% Methane	1	7.062
Steam Exit.Temp	1	3.892

The air-fuel ratio explains most of the TurbineOutput variation
The Regression explains over 98% of the process variation
This Multiple Linear Regression has three statistically significant independent variables
If the air-fuel ratio increases by 1, the TurbineOutput more than triples
The SteamExitTemp explains the most variation of the TurbineOutput

Validate

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