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Question 51

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The Regression Model for an observed value of Y contains the term ?o which represents the Y axis intercept when X = 0.

True
True
False
False
Suggested answer: A
asked 23/09/2024
Charalambos Pasvantis
40 questions

Question 52

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Which statement(s) are true about the Fitted Line Plot shown here? (Note: There are 2 correct answers).

Six Sigma ICGB image Question 52 72647 09232024004316000000

When Reactant increases, the Energy Consumed increases.
When Reactant increases, the Energy Consumed increases.
The slope of the equation is a positive 130.5.
The slope of the equation is a positive 130.5.
The predicted output Y is close to -18 when the Reactant level is set to 6.
The predicted output Y is close to -18 when the Reactant level is set to 6.
Over 85 % of the variation of the Energy Consumed is explained by the Reactant via this Linear Regression.
Over 85 % of the variation of the Energy Consumed is explained by the Reactant via this Linear Regression.
Suggested answer: C, D
asked 23/09/2024
Areeluck Parnsoonthorn
38 questions

Question 53

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After reviewing the Capability Analysis shown here select the statement(s) that are untrue.

Six Sigma ICGB image Question 53 72648 09232024004316000000

The process is properly assumed to be a Normal process
The process is properly assumed to be a Normal process
The Mean of the process moving range is 1.78
The Mean of the process moving range is 1.78
The process is out of Control
The process is out of Control
This Capability Analysis used subgroups
This Capability Analysis used subgroups
Majority of the dimensional values are outside of the tolerance than within
Majority of the dimensional values are outside of the tolerance than within
Suggested answer: A
asked 23/09/2024
Zaid Mohammed Haqqani
33 questions

Question 54

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The actual experimental response data varied somewhat from what a Belt had predicted them to be. This is the result of which of these?

Inefficiency of estimates
Inefficiency of estimates
Residuals
Residuals
Confounded data
Confounded data
Gap Analysis
Gap Analysis
Suggested answer: B
asked 23/09/2024
fritz villanueva
48 questions

Question 55

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Multiple Linear Regressions (MLR) is best used when which of these are applicable? (Note: There are 3 correct answers).

Non-linear relationships between the inputs X's and output Y
Non-linear relationships between the inputs X's and output Y
Uncertainty in the slope of the linear relationship between an X and a Y
Uncertainty in the slope of the linear relationship between an X and a Y
Relationships between Y (output) and more than one X (Input)
Relationships between Y (output) and more than one X (Input)
Preventing the use of a Designed Experiment if unnecessary
Preventing the use of a Designed Experiment if unnecessary
We assume that the X's are independent of each other
We assume that the X's are independent of each other
Suggested answer: C, D, E
asked 23/09/2024
Martin Mannsbarth
32 questions

Question 56

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The generation of a Regression Equation is justified when we _____________. (Note: There are 4 correct answers).

Expect the relationship to be Linear between the output and inputs
Expect the relationship to be Linear between the output and inputs
Know that there is a non-linear relationship between output and input(s)
Know that there is a non-linear relationship between output and input(s)
Need to understand how to control a process output by controlling the input(s)
Need to understand how to control a process output by controlling the input(s)
Experience several process defects and have no other way to fix hem
Experience several process defects and have no other way to fix hem
When it is very expensive or too late to measure the output
When it is very expensive or too late to measure the output
Suggested answer: A, C, D, E
asked 23/09/2024
Natalia Novikova
40 questions

Question 57

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Which statement(s) are correct for the Regression Analysis shown here? (Note: There are 2 correct answers).

Six Sigma ICGB image Question 57 72652 09232024004316000000

This Regression is an example of a Multiple Linear Regression.
This Regression is an example of a Multiple Linear Regression.
This Regression is an example of Cubic Regression.
This Regression is an example of Cubic Regression.
%Cu explains the majority of the process variance in heat flux.
%Cu explains the majority of the process variance in heat flux.
Thickness explains over 80% of the process variance in heat flux.
Thickness explains over 80% of the process variance in heat flux.
The number of Residuals in this Regression Analysis is 26.
The number of Residuals in this Regression Analysis is 26.
Suggested answer: A, D
asked 23/09/2024
Jelle Kamp
41 questions

Question 58

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The Regression Model for an observed value of Y contains the term ?o which represents the Y axis intercept when X = 0.

True
True
False
False
Suggested answer: A
asked 23/09/2024
Lascelles Johnson
38 questions

Question 59

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Which statement(s) are true about the Fitted Line Plot shown here? (Note: There are 2 correct answers).

Six Sigma ICGB image Question 59 72654 09232024004316000000

When Reactant increases, the Energy Consumed increases.
When Reactant increases, the Energy Consumed increases.
The slope of the equation is a positive 130.5.
The slope of the equation is a positive 130.5.
The predicted output Y is close to -18 when the Reactant level is set to 6.
The predicted output Y is close to -18 when the Reactant level is set to 6.
Over 85 % of the variation of the Energy Consumed is explained by the Reactant via this Linear Regression.
Over 85 % of the variation of the Energy Consumed is explained by the Reactant via this Linear Regression.
Suggested answer: C, D
asked 23/09/2024
Sai Janani Ravishankar
35 questions

Question 60

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Select all the statements that are true after reviewing the Capability Analysis shown here. (Note: There are 4 correct answers).

Six Sigma ICGB image Question 60 72655 09232024004316000000

The process is out of Control.
The process is out of Control.
The process is properly assumed to be a Normal process.
The process is properly assumed to be a Normal process.
The Mean of the process moving range is 1.78.
The Mean of the process moving range is 1.78.
This Capability Analysis used subgroups.
This Capability Analysis used subgroups.
Majority of the dimensional values are outside of the tolerance than within.
Majority of the dimensional values are outside of the tolerance than within.
Suggested answer: B, C, D, E
asked 23/09/2024
An Khang Nguyen
48 questions
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