Statistics

@RISK Models
» Bayesian Learning
» Number of Events in Fixed Time
» Random Sum and RiskCompound Function

@RISK Models

Bayesian Learning

This model uses @RISK to illustrate that when several people with different prior beliefs all see the same random outcomes and use Bayes' rule to update their beliefs, they will all converge to the same "truth" in the long run.

Number of Events in Fixed Time

This model uses @RISK simulation to find the distribution of the number of events in a fixed amount of time when the times between events are independent and identically distributed random variables.

Random Sum and RiskCompound Function

This model illustrates how the central limit theorem can be used instead of the RiskCompound function when an output is the sum of a random number of random terms that might be correlated.