11) An acceptance sampling plan’s ability to discriminate between low quality lots and high quality lots is described by: A) a Gantt chart. B) the Central Limit Theorem. C) a process control chart. D) an operating characteristic curve. E) a range chart. 12) Acceptance sampling: A) may involve inspectors taking random samples (or batches) of finished products and measuring them against predetermined standards. B) may involve inspectors taking random samples (or batches) of incoming raw materials and measuring them against predetermined standards. C) is more economical than 100% inspection. D) may be either of a variable or attribute type, although attribute inspection is more common in the business environment. E) All of the above are true. 13) Which of the following statements about acceptance sampling is true? A) Acceptance sampling draws a sample from a population of items, tests the sample, accepts the entire population if the sample is good enough, and rejects it if the sample is poor enough. B) The sampling plan contains information about the sample size to be drawn and the critical acceptance or rejection numbers for that sample size. C) The steeper an operating characteristic curve, the better its ability to discriminate between good and bad lots. D) All of the above are true. E) All of the above are false. 14) Acceptance sampling is usually used to control: A) the number of units of output from one stage of a process that are then sent to the next stage. B) the number of units delivered to the customer. C) the quality of work-in-process inventory. D) incoming lots of purchased products. E) all of the above. 15) An operating characteristic (OC) curve describes: A) how many defects per unit are permitted before rejection occurs. B) the sample size necessary to distinguish between good and bad lots. C) the most appropriate sampling plan for a given incoming product quality level. D) how well an acceptance sampling plan discriminates between good and bad lots. E) none of the above. 16) An operating characteristics curve shows: A) upper and lower product specifications. B) product quality under different manufacturing conditions. C) how the probability of accepting a lot varies with the population percent defective. D) when product specifications don’t match process control limits. E) how operations affect certain characteristics of a product. 17) Producer’s risk is the probability of: A) accepting a good lot. B) rejecting a good lot. C) rejecting a bad lot. D) accepting a bad lot. E) none of the above. 18) Which of the following is true regarding the relationship between AOQ and the true population percent defective? A) AOQ is greater than the true percent defective. B) AOQ is the same as the true percent defective. C) AOQ is less than the true percent defective. D) There is no relationship between AOQ and the true percent defective. E) The relationship between these two cannot be determined. 19) Under which of the following situations will the average outgoing quality (AOQ) decrease? A) The true percentage defective of the lot increases. B) The number of items in the sample decreases. C) The number of items in the lot decreases. D) The probability of accepting the lot for a given sample size and quantity defective increases. E) The difference between the number of items in the lot and the number of items in the sample increases. 20) A Type I error occurs when: A) a good lot is rejected. B) a bad lot is accepted. C) the number of defectives is very large. D) the population is worse than the AQL. E) none of the above