Building Effective Models

Revision as of 17:33, 16 May 2016 by Bbecane (Talk | contribs)

(diff) ← Older revision | Latest revision (diff) | Newer revision → (diff)


Creating useful models is a challenging activity, even for experienced modelers; effective use of influence diagrams can make the process substantially easier and clearer. This chapter provides tips and guidelines from master modelers (including Newton and Einstein) on how to build a model that is effective, one that focuses on what matters, and that is simple, clear, comprehensible, and correct. The key is to start simple and progressively refine and extend the model where tests of initial versions suggest it will be most important.

Most of the material in this chapter, unlike the other chapters in this guide, is not specific to Analytica. These guidelines are useful whether you are using Analytica, a spreadsheet, or any other modeling tool. However, Analytica makes it especially easy to follow these guidelines, using its hierarchical influence diagrams, uncertainty tools, and Intelligent Arrays.

These guidelines have been distilled from many years of experience by master modelers, using Analytica and a variety of other modeling software. However, they are general guidelines, not rules to be adhered to absolutely. We suggest you read this chapter early in your work with Analytica and revisit it from time to time as you gain experience.

Sections

See Also


Comments


You are not allowed to post comments.