Part 2. MM4XL Tools > 1. Strategic Tools > Risk Analyst > 2. Simulation Never heard of it > Interpreting distributions

Risk Analyst

Interpreting distributions

There are two major elements playing a role in the shape of a distribution and, therefore, in its meaning: the range (x- or horizontal axis) and the probability of occurrence (y- or vertical axis). Range and probability of occurrence allow you to set some general rules for interpreting distributions that apply to both risk-adverse and to risk-taker decision-makers.

Rule 1:
When dealing with distributions characterizing variables for which more is better, such as profit or sales, the distribution with the higher values is the most appealing. The example below shows two equally shaped distributions. The one on the right, however, is more appealing because it represents less risk having more positive values. When modeling variables where less is better, such as costs, the distribution on the left would become more appealing.

 Monte Carlo Simulation Software: Management Process Risk Analysis

 Monte Carlo Simulation Software: Management Process Risk Analysis

Rule 2:
Between two distributions with the same range, the distribution with a triangular shape is more appealing than a uniform distribution. The picture below on the right shows a less risky distribution, whilst the uniform likelihood of occurrence of the one on the left makes it less appealing.

 Monte Carlo Simulation Software: Management Process Risk Analysis

 Monte Carlo Simulation Software: Management Process Risk Analysis

Rule 3:
Between two distributions, the one with the greatest range spread is less appealing. The picture below on the right shows a less risky distribution, whilst the larger range of the distribution on the left makes it less appealing.

 Monte Carlo Simulation Software: Management Process Risk Analysis

 Monte Carlo Simulation Software: Management Process Risk Analysis

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