# RESEARCH ARTICLES | RISK + CRYSTAL BALL + ANALYTICS

## Distributions in ModelRisk as Objects (3/8)

As with Crystal Ball, ModelRisk has the ability to fit distributions to historical data. The analyst looking to describe the variation of a Monte Carlo Analysis input can use "fitting" windows to select data and manipulate other options. How does the ModelRisk (MR) fitting experience stack up against the Crystal Ball (CB) methods and options? There are some important differences one should understand about MR before fitting PDFs to the Duke 09_10 Scores spreadsheet.

## Distributions in ModelRisk as Objects (3/8)

As with Crystal Ball, ModelRisk has the ability to fit distributions to historical data. The analyst looking to describe the variation of a Monte Carlo Analysis input can use "fitting" windows to select data and manipulate other options. How does the ModelRisk (MR) fitting experience stack up against the Crystal Ball (CB) methods and options? There are some important differences one should understand about MR before fitting PDFs to the Duke 09_10 Scores spreadsheet.

## Subject Matter Expertise in Distribution Selection (2/8)

Are there discrete univariate probability distribution functions (PDFs) that can be used to simulate college basketball scores? Do we, as avid basketball observers, know enough to suggest one discrete PDF is better than another? In fitting distributions to data in your business problems, the analyst will be asking the same types of questions. If the analyst is not an expert on the inputs and their behavior, he or she should seek out a subject-matter expert (SME) who can provide insight. Putting experience and theoretical knowledge together this way is a best practice for distribution selection.

## Subject Matter Expertise in Distribution Selection (2/8)

Are there discrete univariate probability distribution functions (PDFs) that can be used to simulate college basketball scores? Do we, as avid basketball observers, know enough to suggest one discrete PDF is better than another? In fitting distributions to data in your business problems, the analyst will be asking the same types of questions. If the analyst is not an expert on the inputs and their behavior, he or she should seek out a subject-matter expert (SME) who can provide insight. Putting experience and theoretical knowledge together this way is a best practice for distribution selection.

## Business Analytics: Going the Distance

Business analytics stratifies into three levels of inquiry and findings beginning with descriptive, followed by predictive, and finally prescriptive methods as follows:
• 23 December 2010
• Author: mckibbinusa
• Number of views: 3556