Exam 15: Introduction to Simulation Modeling

Correlation between two random input variables might not change the mean of an output,but it can definitely affect the variability and shape of an output distribution.

A correlation matrix must always have 1's along its diagonal (because a variable is always perfectly correlated with itself)and the correlations between variables elsewhere.

In general,important characteristics of probability distributions include the following distinctions

Which statement is true regarding a simulation model?

It is common in computer simulations to estimate the mean of some distribution by the average of the simulated observations.The usual practice is then to accompany this estimate with a confidence interval,which indicates the accuracy of the estimate.

One important special case of bounded distributions is when the only possible values are

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

We can think of the uniform distribution as

It is usually not too difficult to predict the shape of the output distribution from the shape(s)of the input distribution(s).

Many companies have used simulation to determine which of several possible investment projects they should choose.This is often referred to as

The normal distribution is often used in simulation models because it is the most common distribution in statistics and it does not allow negative values.

When determining the most appropriate input probability distribution in a simulation model,first select the most appropriate family,and then select the most appropriate member of that family.

The uniform distribution is bounded by a minimum and a maximum,and all values between these two extremes are equally likely.

When we maximize or minimize the value of a decision variable by running several simulations simultaneously,we have found an optimal solution to the problem and attitude toward risk becomes irrelevant.

A continuous probability distribution is characterized by a

The triangular distribution is sometimes used in simulation models because it is more flexible and intuitive than the normal distribution.

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

Simulation models are particularly useful for

Different random numbers generated by the computer are probabilistically dependent.This implies that when we generate a random number in a particular cell,it has some effect on the values of any other random numbers generated in the spreadsheet.

Which of the following statements are true?