Question 26
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
- Uncertainty in the slope of the linear relationship between an X and a Y
- Relationships between Y (output) and more than one X (Input)
- Preventing the use of a Designed Experiment if unnecessary
- We assume that the X’s are independent of each other
Question 27
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
- 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)
- Experience several process defects and have no other way to fix them
- When it is very expensive or too late to measure the output
Question 28
Which statement(s) are correct for the Regression Analysis shown here? (Note: There are 2 correct answers).
- Regression is an example of a Multiple Linear Regression.
- This Regression is an example of Cubic Regression.
- %Cu explains the majority 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.
Question 29
The Regression Model for an observed value of Y contains the term to which represents the Y axis intercept when X = 0.
- True
- False
Question 30
Which statement(s) are true about the Fitted Line Plot shown here? (Note: There are 2 correct answers).
- When Reactant increases, the Energy Consumed increases.
- 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.
- Over 85 % of the variation of the Energy Consumed is explained by the Reactant via this Linear Regression.