Exam 15: Introduction to Simulation Modeling

Company experts believe the development time will be from 5 to 9 months.They believe that 7 months is twice as likely as either 6 months or 8 months and that either of these latter possibilities is three times as likely as either 5 months or 9 months.

The binomial distribution can be well approximated by the normal distribution when the number of trials n is sufficiently small and the probability of success p is not too close to 0 or 1.

A continuous probability distribution is characterized by a:

If we want to model a random stock price,we should do so with an unbounded symmetric probability distribution.

A probability distribution is bounded if there are values A and B such that:

(A)The three stock returns are highly correlated.The correlation between each pair is 0.9 (B)The three stock returns are practically independent.The correlation between each pair is 0.1 (C)The first two stocks are moderately correlated.The correlation between their returns is 0.4.The third stock's return is negatively correlated with the other two.The correlation between its return and each of the first two is -0.8. (D)Compare the portfolio distributions from @RISK for the three scenarios in (A),(B)and (C).What do you conclude? (E)You might think of a fourth scenario,where the correlation between each pair of returns is a large negative number such as -0.80.But explain intuitively why this makes no sense.Try running a simulation with these negative correlations to see what happens.

Which of the following statements are false?

Simulation models are particularly useful for:

When you try to find the most appropriate input probability distribution in a simulation model,you first have to choose the most appropriate family,and then you have to select the most appropriate member of that family

A discrete distribution is useful for many situations,either when the uncertain quantity is not really continuous (the number of televisions demanded,for example)or when you want a discrete approximation to a continuous variable.

Which of the following statements are true?

Which of the following statements are false regarding the graph of a continuous probability distribution?

(A)What fraction of the random numbers are smaller than 0.5? (B)What fraction of the time is a random number less than 0.5 followed by another random number less than 0.5? (C)What fraction of the random numbers are larger than 0.8? (D)What do you expect the answers to (A),(B)and (C)to be before simulating? Do the answers you provided to those questions match your expectations? Explain why or why not. (E)Suppose your answers to (A),(B)and (C)are not close to the expected answers.What can you do to obtain answers from the simulation that are closer to the expected answers?

Which of the following statements are false regarding the numbers generated by the RAND function in Excel?

Which of the following statements is correct regarding the graph of a discrete probability distribution?

When n is reasonably large and p isn't too close to 0 or 1,the binomial distribution can be well approximated by which of the following distributions?

(A)Use simulation to determine how many cars the dealer should order in August,2009 to maximize his expected profit. (B)For the optimal order quantity,find a 95% confidence interval for the expected profit. (C)Why is it important to develop the confidence interval in (B)?

Which of the following statements is (are)false regarding the numbers generated by the RAND function in Excel?

If a model contains uncertain outputs,it can be very misleading to build a deterministic model by using the means of the inputs to predict an output.This is called the:

When we run simulation,the @Risk automatically keeps statistics such as averages and standard deviations,and can also create graphs such as histograms based on the values generated in the output cells in the simulation model.