Answer some questions for six sigma

Qualitative Questions 1. Briefly explain what CTQs are and give some examples of CTQs from service or manufacturing industry 2. Give examples for continuous and discrete data 3. Briefly explain some of the data collection methods 4. Why do we need to sample? Isn’t it more accurate to go check all the items and make a decision? 5. What are the sampling and non-sampling errors? Can you give some examples for each of them? 6. What are random stratified sampling methods? Can you explain when one should use stratified sampling? 7. Please explain why we divide the sum of squared differences by n-1 when we compute the standard deviation for the sample 8. What are the descriptive statistics (such as mean, forth spread, range, variance, median, and mode) that measure variation? 9. Which descriptive statistics are more resilient to outliers? 10. What are the causes of variation? (Common causes vs. Special causes). Explain these causes with examples from industry 11. Why do we conduct a Gage R&R study? 12. Explain the concepts below with examples a. Reproducibility b. Repeatability c. Product variation 13. Define what benchmarking is and please research the benefits of benchmarking Quantitative Questions 1. Download the “Bolts” dataset. This dataset represents bolts and their diameters from a manufacturing shop. The mean of the bolts are known and equal to 9.89. The upper and lower specification limits respectively are 10.70 and 9.63. Please compute the process capability. 2. In a fast food restaurant, you select a sample of bills with a sample size of 80. You observe that 12 of the bills have errors. a. Find DPMO b. Find Defect % c. Find Yield % d. Find the process sigma. 3. In order to decrease the infections after operations, we would like to estimate the average post-op infection counts of the orthopedics department at a hospital. How many patients must we randomly select to be 99 percent sure that the sample mean is within 1 unit of the population mean. Assume that we know the standard deviation of the infection rates based on our previous knowledge. σ= 3.5 infections.