1. Which is the following reason(s) indicate(s) why it is often better to t an input model rather than reusing just reusing the data (multiple choice).

(a). There may be gaps in which values are possible, but none occurred in this particular sample.

(b) There may be collections of values that are overrepresented, just by chance.

(c) Highly unusual events do not occur very often; therefore, they may not be appropriately represented in a sample of data, particularly if the sample size is. As a result, a simulation model that does not include the chance of extreme events will not correctly represent the risks to the system.

(d) By fitting an input model, you can infer the tail behavior that may not be present in the data.

(e) With a parametric input model (a probability distribution) you can change its parameters, or even select a new distribution, to reflect the changes.

2.Which of the following statements is WRONG about goodness-of-fit (gof)

(a)A good fit occurs when an input model represents the key features of the real process that have a significant impact on the simulation output measures of interest.

(b)If you fail to reject the test, you conclude that the selected distribution is selected wrong and does not statistically fit to data.

(c)The more data that are available, the easier it is for the test to deduce that you are wrong. if you do not have much data then almost any choice will be accepted by the test.

(d)Before you run the test, you know that your model choice is wrong!.

(e)A large p-value supports your choice of input model, and p-values greater than 0:10 are typically considered to be "large".

3. Input processes that change over time are said to be nonstationary. A generalization of the Poisson arrival process allows the arrival rate to vary with time. Such a process is called a nonstationary or nonhomogeneous Poisson arrival process. Which of the following examples can NOT be considered as a nonstationary process/system?

(a)Customer arrivals to a restaurant (during the whole day)

(b)The times of discovery of bugs in a software product

(c)Production rate in an assembly line in a specific shift

(d) Arrival of text messages to a mail server in a day