If it don't fit, don't force it

In this article, I discussed univariate probability modeling techniques, including fitting data to a theoretical probability distribution and using the fitted theoretical probability distribution to assign probabilities to various outcomes. I provided a sample model (of soccer goals) to demonstrate the efficacy of this basic form of probability modeling and served up a tool to help construct probability models, a Probability Distributions Library. And you started building the foundation for understanding and developing more complex forms of probability models.

In conclusion, the following are some random variables for which you might want to construct probability models as practice:

• The time interval between customer orders
• The number of customer orders in a given week
• The number of people purchasing a particular product in a given week
• The time interval between purchases of a particular product
• The number of visitors to your Web site at any given minute, hour, or day

The Exponential and Poisson distributions included in the PHPMath_ProbabilityDistribution package are particularly suitable for investigating these random variables further.