How to Use the Custom Distribution in Crystal Ball – The Discrete Distribution
(Tip #2 of 5)

The following Risk Analysis Tip is provided by Dr. H. Groenendaal (Huybert@risk-modeling.com) at Vose Consulting, and has been drawn from material in ModelAssist® for Crystal Ball®, the comprehensive risk analysis training, reference and template software. ModelAssist users can consult the ModelAssist-references (in the form of Mxxx) for additional information. To read more about ModelAssist and get a free download of the demo version, click here or go to http://www.decisioneering.com/modelassist/index.html.

Introduction

The Custom Distribution in Crystal Ball is one of the most versatile, but also one of the most difficult distributions to correctly use within Crystal Ball. In fact, using the Custom Distribution, a Crystal Ball user can construct five different kinds of distributions (see Table below).

Each of these five distributions have different uses and applications. The way that the Custom distribution “knows” which of the above five to make for you totally depends on the format of your input data ("date entry rules").

The goal of this (and the last tip and the next three) Risk Analysis tip(s) is to make you aware of the five different distributions that you can construct using the Custom Distribution and their various uses. The five Tips will also provide detailed instructions on how to format your data to construct the five different distributions with the Custom Distribution.

Important Note – Dynamic Referencing

When you use the Custom Distribution, we highly recommend that you use data from your spreadsheet and use “dynamic referencing” with the Custom Distribution because this allow the user to change data in his/her spreadsheet, which will result in appropriate changes in the distributions. You can read more about that in the Previous Risk Analysis Tip (Tip 1 of 5) .

1. The Discrete distribution.

The Discrete Uniform distribution is often used for:

1. Probability branching,
2. Combining expert opinion and,
3. Construction of a user-defined discrete distribution.

For information about applications of the Discrete Distribution, see ModelAssist topic M0129.

The discrete distribution is a general type of function used to describe a variable that can take one of several explicit discrete values {x_i} and where a probability weight {p_i} is assigned to each value (see M0129 for uses of this distribution). There are two methods to modeling a Discrete distribution with Crystal Ball's Custom Distribution, as is shown below:

Method 1

The first and most flexible way is to provide the Custom Distribution with two columns; the left one with the values of your parameter and the right one with the probability weight of each value (C12:D18).

Method 2

In the second method, we provide the Custom Distribution with four columns as shown below; the first cell gives the first value of each bin (row), and the second cell the last value of each bin. The third cell is the probability of being in that specific bin and the fourth finally gives the steps between the different data points within the specific bin as shown below.

What’s next?

If you like to know more about the Custom Distribution (or about Quantitative Risk Analysis in general), download the free demo of ModelAssist for Crystal Ball. This comprehensive risk analysis reference and training tool will help you perform accurate risk analyses with the Crystal Ball software.

ModelAssist

The material within this ‘Risk Analysis Tip’ comes from one of the over 500 risk analysis topics available in ModelAssist for Crystal Ball, which gives a more detailed explanation of the above methods and any risk analysis techniques involved.

> Learn more about ModelAssist for Crystal Ball