mytest > help > Part 2. MM4XL Tools > 1. Strategic Tools > Risk Analyst > 4. Functions > 3. Distribution Functions > mmBINOMIAL(Trials, Successes)

Risk Analyst

mmBINOMIAL(Trials, Successes)

Example

=mmBINOMIAL(5, 0.5) can equal 3

Application

This function is used to determine the number of events that occur given a certain probability of occurrence. There are only two possible outcomes for each trial, true/false, pass/fail, etc. The trials are independent, which means previous trials have no effect on successive trials. The probability of occurrence does not change between trials.

How to use

This function returns the number of events that occur. This helps, for instance, when we need to estimate the entrance of a new competitor in the market.

Say that we are launching a new product in a new market category and we need a model to estimate the profitability over the next 5 years. We expect competition to enter the category, and based on previous knowledge we estimate a maximum number of 5 competitors to enter the category in 5 years with a probability of 40% for these events to occur. The formula below estimates the number of competitors entering the market in one year:
=mmBINOMIAL(5, 0.4)

Copy the formula above in 100 cells. You will find that the maximum value will be 5, as the number of competitors that we expect, and most estimates (about two thirds) suggest the entry of one to two new competitors. If we were modeling the outcome of a new product launch, we should use a limiting factor across the years in order to avoid the entrance of more than 5 players in the given period of time.

Technical profile

Type Discrete distribution.
Syntax =mmBINOMIAL(Trials, Successes)
Domain RndNum = integer
 Monte Carlo Simulation Software: Management Process Risk Analysis.
Mode Integer =  Monte Carlo Simulation Software: Management Process Risk Analysis
Otherwise =  Monte Carlo Simulation Software: Management Process Risk Analysis
Parameters Trials is the number of independent trials.
Successes is the number of successes in trials.
Remarks If any argument is nonnumeric mmBINOMIAL returns the #VALUE! error value.
Relationships It is related to the Beta, Hypergeometric, Negative Binomial, Normal, Poisson and to the Students t variates.
Graphs
mmBINOMIAL(5, 0.5) mmBINOMIAL(20, 0.5)
 Monte Carlo Simulation Software: Management Process Risk Analysis  Monte Carlo Simulation Software: Management Process Risk Analysis
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