ISYE 6644 2 PRACTICE EXAMINATION 2026
QUESTIONS WITH ANSWERS GRADED A+
◍ (Lesson 8.2: Identifying Distributions.) Name That Distribution!IQsa.
Uniformb. Normalc. Exponentiald. Weibulle. Pareto.
Answer: b. Normal
◍ What are internal variables.
Answer: Arena keeps track of and continuously updates lots of stuff as the
simulation runsExamples:TNOW (current sim time)NR(Barber) - # of
resource Barber's servers now workingNQ(Process 1.Queue) = # of
customers in that queueCreate 1.NumberOut = # of customers who have so
far left the module Create 1
◍ What type of Seize selection rules are possible for sets?.
Answer: Cyclical, Random, Preferred Order, Specific Member, Largest
Remaining Capacity
◍ (9.4) TRUE or FALSE? You can also conduct finite-horizon estimation for
quantities other than expected values, e.g., simulate a bank from 8:00 a.m. to
5:00 p.m., and find a confidence interval for the 95th quantile of customer
waiting times..
Answer: True
◍ What sort of options/tab can you change in run setup?.
Answer: Replications, run speed, reports, run control
◍ (8.10/8.11) The test statistic is χ0^2 = 9.12. Now, let's use our old friend α =
0.05 in our test. Let k = 4 denote the number of cells (that we ultimately
ended up with) and let s = 1 denote the number of parameters we had to
estimate. Then we compare against χ^2(α=0.05 , k − s − 1) = χ^2(α=0.05 , 2)
= 5.99. Do we ACCEPT (i.e., fail to reject) or REJECT the Geometric
hypothesis?.
, Answer: Reject. The test statistic 9.12 is not less than 5.99.
◍ What does separate do.
Answer: Duplicates a single entity or split multiple entities that have been
combined in a Batch module. If dealing with a permanent batch, usually use
duplicate original to get several customers all with the same attributes. If
temp batch, use split to get original attributes
◍ (8.6) TRUE or FALSE? Sometimes it might be difficult to obtain an MLE in
closed form..
Answer: True. (There is a gamma example.)
◍ (8.4) Suppose that estimator A has bias = 3 and variance = 12, while
estimator B has bias -2 and variance = 14. Which estimator (A or B) has the
lower mean squared error?.
Answer: B is lower. Bias^2 + Variance: 18 < 21
◍ (10.2) "Assume unknown variance sigma^2". Probably will use
t-distribution..
Answer: True.
◍ Attribute spreadsheet.
Answer: The attribute spreadsheet keeps track of existing attributes that you
might define in an Assign
◍ True or False? a = P(Reject H0 | H0 is true) is the probability of a Type 1
error.
Answer: True
◍ What tests do we perform on PRNs?.
Answer: Goodness-of-fit tests - are the PRN's approx
Unif(0,1)?Independence tests - are the PRN's approximately independent?
◍ What are variables?.
Answer: Unlike attributes, whose values are specific to each customer,
variables are global. If changed, it gets changed everywhere e.g. WIP
◍ What can go wrong with LCGs?.
, Answer: Some are not full periodSome produce very non-random outputIf m
is small (< 2 bil) you'll get quick cyclingEven if m is big, some problems
can arise (RANDU)
◍ (8.9) Suppose we're conducting a χ^2 goodness-of-fit test with Type I error
rate α = 0.01 to determine whether or not 100 i.i.d. observations are from a
lognormal distribution with unknown parameters μ and σ^2. If we divide the
observations into 5 equal-probability intervals and we observe a g-o-f
statistic of χ0^2 = 11.2, will we ACCEPT (i.e., fail to reject) or REJECT the
null hypothesis of lognormality?.
Answer: Reject. k = 5, subtract 1 and subtract 2 for the two unknown
parameters (or had to estimate), so degrees of freedom is 2. critical value for
dof 2 and alpha 0.01 is 9.21. 11.2 is not smaller than 9.21 so we reject it.
Not a good fit.
◍ (10.16) Suppose that we want to know which of Coke, Pepsi, and Dr. Pepper
is the most popular. We would like to make the correct selection with
probability of at least P =0.90 in the event that the ratio of the
highest-to-second-highest preference probabilities happens to be at least
θ =1.4. How many people does the single-stage procedure M{BEM}
require us to interview?.
Answer: From table, find P = 0.9, Theta = 1.4 and k = 3 competitors
◍ True or False? You can find individual Seize, Delay, and Release module in
this template..
Answer: True
◍ Record Module.
Answer: -Collect statistics when an entity passes through the module
◍ True or False? It's possible to request servers in a set randomly, cyclically,
or according to some priority characteristic (such as the order in which they
are placed in the set).
Answer: True
◍ (9.6) Which scenarios might be well-suited for a steady-state analysis?.
QUESTIONS WITH ANSWERS GRADED A+
◍ (Lesson 8.2: Identifying Distributions.) Name That Distribution!IQsa.
Uniformb. Normalc. Exponentiald. Weibulle. Pareto.
Answer: b. Normal
◍ What are internal variables.
Answer: Arena keeps track of and continuously updates lots of stuff as the
simulation runsExamples:TNOW (current sim time)NR(Barber) - # of
resource Barber's servers now workingNQ(Process 1.Queue) = # of
customers in that queueCreate 1.NumberOut = # of customers who have so
far left the module Create 1
◍ What type of Seize selection rules are possible for sets?.
Answer: Cyclical, Random, Preferred Order, Specific Member, Largest
Remaining Capacity
◍ (9.4) TRUE or FALSE? You can also conduct finite-horizon estimation for
quantities other than expected values, e.g., simulate a bank from 8:00 a.m. to
5:00 p.m., and find a confidence interval for the 95th quantile of customer
waiting times..
Answer: True
◍ What sort of options/tab can you change in run setup?.
Answer: Replications, run speed, reports, run control
◍ (8.10/8.11) The test statistic is χ0^2 = 9.12. Now, let's use our old friend α =
0.05 in our test. Let k = 4 denote the number of cells (that we ultimately
ended up with) and let s = 1 denote the number of parameters we had to
estimate. Then we compare against χ^2(α=0.05 , k − s − 1) = χ^2(α=0.05 , 2)
= 5.99. Do we ACCEPT (i.e., fail to reject) or REJECT the Geometric
hypothesis?.
, Answer: Reject. The test statistic 9.12 is not less than 5.99.
◍ What does separate do.
Answer: Duplicates a single entity or split multiple entities that have been
combined in a Batch module. If dealing with a permanent batch, usually use
duplicate original to get several customers all with the same attributes. If
temp batch, use split to get original attributes
◍ (8.6) TRUE or FALSE? Sometimes it might be difficult to obtain an MLE in
closed form..
Answer: True. (There is a gamma example.)
◍ (8.4) Suppose that estimator A has bias = 3 and variance = 12, while
estimator B has bias -2 and variance = 14. Which estimator (A or B) has the
lower mean squared error?.
Answer: B is lower. Bias^2 + Variance: 18 < 21
◍ (10.2) "Assume unknown variance sigma^2". Probably will use
t-distribution..
Answer: True.
◍ Attribute spreadsheet.
Answer: The attribute spreadsheet keeps track of existing attributes that you
might define in an Assign
◍ True or False? a = P(Reject H0 | H0 is true) is the probability of a Type 1
error.
Answer: True
◍ What tests do we perform on PRNs?.
Answer: Goodness-of-fit tests - are the PRN's approx
Unif(0,1)?Independence tests - are the PRN's approximately independent?
◍ What are variables?.
Answer: Unlike attributes, whose values are specific to each customer,
variables are global. If changed, it gets changed everywhere e.g. WIP
◍ What can go wrong with LCGs?.
, Answer: Some are not full periodSome produce very non-random outputIf m
is small (< 2 bil) you'll get quick cyclingEven if m is big, some problems
can arise (RANDU)
◍ (8.9) Suppose we're conducting a χ^2 goodness-of-fit test with Type I error
rate α = 0.01 to determine whether or not 100 i.i.d. observations are from a
lognormal distribution with unknown parameters μ and σ^2. If we divide the
observations into 5 equal-probability intervals and we observe a g-o-f
statistic of χ0^2 = 11.2, will we ACCEPT (i.e., fail to reject) or REJECT the
null hypothesis of lognormality?.
Answer: Reject. k = 5, subtract 1 and subtract 2 for the two unknown
parameters (or had to estimate), so degrees of freedom is 2. critical value for
dof 2 and alpha 0.01 is 9.21. 11.2 is not smaller than 9.21 so we reject it.
Not a good fit.
◍ (10.16) Suppose that we want to know which of Coke, Pepsi, and Dr. Pepper
is the most popular. We would like to make the correct selection with
probability of at least P =0.90 in the event that the ratio of the
highest-to-second-highest preference probabilities happens to be at least
θ =1.4. How many people does the single-stage procedure M{BEM}
require us to interview?.
Answer: From table, find P = 0.9, Theta = 1.4 and k = 3 competitors
◍ True or False? You can find individual Seize, Delay, and Release module in
this template..
Answer: True
◍ Record Module.
Answer: -Collect statistics when an entity passes through the module
◍ True or False? It's possible to request servers in a set randomly, cyclically,
or according to some priority characteristic (such as the order in which they
are placed in the set).
Answer: True
◍ (9.6) Which scenarios might be well-suited for a steady-state analysis?.
