Design of Experiments
About the Lecture
The lecture Design of Experiments by Grey Campus is from the course Six Sigma Green Belt Training. It contains the following chapters:
- Types of DoE
- Maruti Case Study
- DoE Terminologies
- DoE
- DoE - Basic Terms
- Tree Diagram
Included Quiz Questions
The p values for the variables denotes whether
- The particular variable has an impact on Y or not
- Indicates the presence of random variation
- Can indicate presence of experimental errors
- None of them
Residual error indicates
- None of them
- Left over errors
- Error in calculations
- Rounding off errors
Which of the below terms help us to find out if we have left out a critical X variable?
- the Residual error
- The coefficient
- The effect
- The constant
The pre-requisite for analyzing a DOE is
- None of them
- the Y data should be Normal
- the Y data should have minimal variation
- Mean of Y should not be greater than the minimum value of Y
Main effects plot gives us
- The impact of the variable on the Y
- Plot of all the variables Vs. Y
- An indication of how the variables are interacting among themselves
The deciding criteria for understanding the main effect plot is
- The slope of the line in the graph
- The length of the graph
- The length of the X axis
- The length of the Y axis
Interaction plot gives us
- An indication of how the variables are interacting among themselves
- The impact of the variable on the Y
- Plot of all the variables Vs. Y
A negative value for a coefficient indicates
- As the value of the variable increases, Y decreases
- There is something wrong in the experimentation
- As the value of the variable increases, Y increases
- We have to redo the experiments
If the absolute value of a coefficient is 2345, it means that
- Cannot say, till we look at the p values and the values of coefficients of other variables
- It has a very high impact on the Y
- It has a very low impact on the Y
- It has to be ignored
Experiments should be run in the following order
- Run order
- Standard order
- Random order
The number of experiments in a two level design is determined by
- 2 raised to number of variables
- Number of variables raised to 2
- 2 raised to number of variables divided by 2
DOE is used after
- Critical factors are identified through hypothesis testing
- There is at least one continuous variable
- Variable levels can be set at low and high
- None of them
Which of the following tools helps us to understand the interaction effects of variables?
- Factorial experiments
- Hypothesis testing
- Simple regression
How many experiments will need to be conducted when you have 5 variables and 2 levels each, with no replication?
- 32
- 16
- 48
- 64
How many experiments will need to be conducted when you have 6 variables and 2 levels each, with replication?
- 128
- 64
- 96
- 256
Author of lecture Design of Experiments
Grey Campus
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