An asterisk on the problem number indicates

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Reference no: EM131075903

11.1. Consider a typical hospital emergency room.

a. Describe why it is a queueing system.

b. What is the queue in this case? Describe how you would expect the queue discipline to operate.

c. Would you expect random arrivals?

d. What are service times in this context? Would you expect much variability in the service times?

Question 12.1)The symbols to the left of some of the problems (or their parts) have the following meaning:

E*: Use Excel.

Q*: Use the Queueing Simulator.

An asterisk on the problem number indicates that at least a partial answer is given in the back of the book.

12.1.* Use the random numbers in cells C13:C18 of Figure 12.1 to generate six random observations for each of the following situations.

a. Throwing an unbiased coin.

b. A baseball pitcher who throws a strike 60 percent of the time and a ball 40 percent of the time.

c. The color of a traffic light found by a randomly arriving car when it is green 40 percent of the time, yellow 10 percent of the time, and red 50 percent of the time.

Below is the answer on the back of the book

12.1.   b. Let the numbers 0.0000 to 0.5999 correspond to strikes and the numbers 0.6000 to 0.9999 correspond to balls. The random observations for pitches are 0.3039 = strike, 0.7914 = ball, 0.8543 = ball, 0.6902 = ball, 0.3004 = strike, 0.0383 = strike.

12.1) Figure

The Probability Distribution of Breakdowns for Heavy Duty's Motors, and the Corresponding Random Numbers Corresponding Random Numbers

Day                      Probability of a Breakdown                    Corresponding Random #

1,2,3                                         0                                                       

4                                            0.25                                                     0.0000 to 0.2499

5                                            0.5                                                       0.2500 to 0.7499

6                                           0.25                                                      .7500 to 0.9999

7or more                                  0

12.7.    Generate three random observations from the uniform distribution between - 10 and 40 by using the following random numbers: 0.0965, 0.5692, 0.6658.

Reference no: EM131075903

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