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Six Sigma ICBB Practice Test - Questions Answers

List of questions

Question 1

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A Non-parametric Test should be used if just one distribution is not Normal out of the two or more gathered.

True
True
False
False
Suggested answer: A
asked 23/09/2024
Manoj Balan
44 questions

Question 2

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Contingency Tables are used to test for association, or dependency, between two or more classifications.

True
True
False
False
Suggested answer: A
asked 23/09/2024
Eduardo Bravo
38 questions

Question 3

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For the data shown here which statement(s) are true? (Note: There are 2 correct answers).

Six Sigma ICBB image Question 3 72229 09232024004306000000

With 95% confidence, we cannot conclude if the samples are from three Normal Distributions.
With 95% confidence, we cannot conclude if the samples are from three Normal Distributions.
With greater than 95% confidence, we conclude the samples are from Non-normal Distributions.
With greater than 95% confidence, we conclude the samples are from Non-normal Distributions.
If we wanted to compare the Central Tendencies of these three samples we would use the one way ANOVA test.
If we wanted to compare the Central Tendencies of these three samples we would use the one way ANOVA test.
If we wanted to compare the Central Tendencies of these three samples we could use Mood's Median test.
If we wanted to compare the Central Tendencies of these three samples we could use Mood's Median test.
Suggested answer: B, D
asked 23/09/2024
Ibrahim SACCA
38 questions

Question 4

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Choose those characteristics of a Simple Linear Regression (SLR) Analysis that are applicable. (Note: There are 3 correct answers).

The Correlation Coefficient is always greater than the Regression Coefficient in a SLR
The Correlation Coefficient is always greater than the Regression Coefficient in a SLR
General Regression Analysis deals only with Continuous Data
General Regression Analysis deals only with Continuous Data
Non-linear Regressions can explain curvature when with more statistical confidence than Linear Regressions
Non-linear Regressions can explain curvature when with more statistical confidence than Linear Regressions
SLR can help quantify the significance of variation in X that influences the variation in Y via a mathematical equation
SLR can help quantify the significance of variation in X that influences the variation in Y via a mathematical equation
A Correlation does not explain causation but a Regression Analysis with a statistically valid mathematical equation does explain causation
A Correlation does not explain causation but a Regression Analysis with a statistically valid mathematical equation does explain causation
Suggested answer: A, D, E
asked 23/09/2024
test testsers
39 questions

Question 5

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A valid Multiple Linear Regression (MLR) is characterized by all of these except?

It is an assumption that the X's (inputs) are not correlated to each other
It is an assumption that the X's (inputs) are not correlated to each other
The X's (inputs) are assumed to be independent of each other
The X's (inputs) are assumed to be independent of each other
The Residuals from MLR analysis have to be Normally Distributed
The Residuals from MLR analysis have to be Normally Distributed
MLR is conducted based on a deliberate form of experimentation
MLR is conducted based on a deliberate form of experimentation
It is not possible to evaluate interactions in a MLR analysis
It is not possible to evaluate interactions in a MLR analysis
Suggested answer: D
asked 23/09/2024
Helania Stevenson
51 questions

Question 6

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Which statement is NOT correct about the Fitted Line Plot shown here?

Six Sigma ICBB image Question 6 72232 09232024004306000000

The independent variable is the reactant
The independent variable is the reactant
If the reactant was 10 units, with 95% confidence we would expect a minimum yield of 148 units
If the reactant was 10 units, with 95% confidence we would expect a minimum yield of 148 units
With at least 95% confidence, we can expect less than 10 units of Yield when the reactant is at a value of 1
With at least 95% confidence, we can expect less than 10 units of Yield when the reactant is at a value of 1
A reactant value between 6 and 8 units yields around 40 to 60
A reactant value between 6 and 8 units yields around 40 to 60
When the reactant increases, the expected yield would increase
When the reactant increases, the expected yield would increase
Suggested answer: D
asked 23/09/2024
Rafal Piasecki
40 questions

Question 7

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The calculation of Column Total times Row Total divided by Grand Total yields expected values from what type of chart?

Pareto Chart
Pareto Chart
Sakami Table
Sakami Table
Contingency Table
Contingency Table
None
None
Suggested answer: C
asked 23/09/2024
mahdis khaledi
46 questions

Question 8

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Contingency Tables are used to test for association, or dependency, between two or more classifications.

True
True
False
False
Suggested answer: A
asked 23/09/2024
Alessandro Cristofori
39 questions

Question 9

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It would be more likely than not for a Belt conducting a Regression Analysis to find that the _______________________.

r2 value is smaller than the absolute value of r
r2 value is smaller than the absolute value of r
Correlation Coefficient equals r2
Correlation Coefficient equals r2
Coefficient of Determination is less than r2
Coefficient of Determination is less than r2
Correlation Coefficient equals r divided by 2
Correlation Coefficient equals r divided by 2
Suggested answer: A
asked 23/09/2024
Khuong Tang
31 questions

Question 10

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A valid mathematical Regression represents all of the characteristics shown except _________________.

All of the standardized residuals will be within 3 Standard Deviations
All of the standardized residuals will be within 3 Standard Deviations
The sum of the residuals is zero
The sum of the residuals is zero
The residuals when plotted follow a Normal Distribution
The residuals when plotted follow a Normal Distribution
Most standardized residuals are within 2 Standard Deviations
Most standardized residuals are within 2 Standard Deviations
The Residual is equal to the difference between the observed and predicted values
The Residual is equal to the difference between the observed and predicted values
Suggested answer: A
asked 23/09/2024
ALBERTO BONATO
46 questions
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