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Quantitative Analysis BA 452 Supplemental Questions 9 This document contains practice questions that supplement review questions for Lessons II-7 and II-8. This document first identifies the learning objectives of solving supplemental questions. The document then lists 35 questions and answers. All questions can be helpful. Questions marked with an asterisk * are similar to review questions. Tip: Supplemental questions are grouped into sets of similar type. Once you have mastered the questions in a set, you can skip the rest of the questions in that set. 1 Quantitative Analysis BA 452 Supplemental Questions 9 Objectives By working through the homework questions and the supplemental questions, you will: 1. Be able to identify where…show more content…
a. What is the probability that no requests for assistance are in the system? b. What is the average number of requests that will be waiting for service? c. What is the average waiting time in minutes before service begins? d. What is the average time at the reference desk in minutes (waiting time plus service time)? e. What is the probability that a new arrival has to wait for service? 6. Movies Tonight is a typical video and DVD movie rental outlet for home viewing customers. During the weeknight evenings, customers arrive at Movies Tonight with an arrival rate of 1.25 customers per minute. The checkout clerk has a service rate of 2 customers per minute. Assume Poisson arrivals and exponential service times. a. What is the probability that no customers are in the system? b. What is the average number of customers waiting for service? c. What is the average time a customer waits for service to begin? d. What is the probability that an arriving customer will have to wait for service? e. Do the operating characteristics indicate that the one-clerk check out system provides an acceptable level of service? 7. Speedy Oil provides a single-channel automobile oil change and lubrication service. Customers provide an arrival rate of 2.5 cars per hour. The service rate is 5 cars per hour. Assume that arrivals follow a Poisson probability distribution and that service times follow an exponential probability distribution. a. What