Provide support for your response by citing from the readings or other scholarly writings.
1. Discuss measurement system discrimination and the concept of data categories. Why should a measurement system be able to divide a region of interest into at least five categories?
2. Compare stability with reproducibility. How are they similar and how are they different?
3. Evaluate the statement, “a gage can be perfectly accurate when checking a standard and still be entirely unacceptable for measuring a product or controlling a process.” Provide a example.
4. Discuss the statement, “Once statistical stability has been achieved, but not before, measurement system stability can be determined.” If control charts are the best means for determining statistical stability, why must the measurement system stability be after it? Shouldn’t you know first if the measurement system is capable of discrimination?
5. Compare design-based inferences to model-based inferences and relate these to the concept of external validity. Give an example of each type of inference as it relates to SPC.
6. Explain and discuss hypothesis testing as it relates to the null and alternative hypothesis and the types of error associated with inferential statistics. How does power and sample size affect hypothesis testing?
7. Explain the idea of data space as applied to the study of independent variables. Give a real-world example of this.
8. Why are designed experiments with replication more powerful than other types of DOE? Give an example.
9. Discuss the various methods in use today for testing the normality of data. Which ones are most useful?
10. Describe some applications for the use of non-parametric methods. What are the advantages and disadvantages of non-parametric methods?