If you don’t read manuals

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Experienced modelers find most Analytica features intuitive. But, it’s helpful to get a good grasp of some key concepts so you can get up to speed rapidly. Here are a few chapters that you might find especially helpful to review.

Chapter Contents
Building Effective Models Guidelines distilled from the experience of master modelers. It offers practical suggestions for building models that are clear, reliable, and focus on what really matters — the decisions, objectives, and key uncertainties. These tips are not specific to Analytica, but we designed Analytica to make them especially easy to follow.
Creating Lucid Diagrams Tips on how to avoid producing incomprehensible spaghetti -- and create influence diagrams that are truly lucid and even elegant.
Arrays and Indexes We especially recommend this section for people who don't read manuals, including -- perhaps especially - experienced modelers! Once you grasp the essentials of Analytica’s Intelligent Arrays™, you'll find that you can build complex multidimensional models with surprising ease. But, at first, you might find they take a little getting used to, particularly if you have spent a lot of time with spreadsheets or programming with arrays.
Expressing Uncertainty How to select appropriate probability distributions to express uncertainties. It also provides an overview of how Analytica computes probability distributions using Monte Carlo and other random sampling methods, and your options for displaying probabilistic values.
Procedural Programming Analytica is a "declarative" language, enabling you to create large and sophisticated models without conventional procedural programming. But, sometimes you really want to write complex procedural functions. If so, read this chapter to understand Analytica as a programming language.

See Also



23 months ago
Score 0

Should the paragraph on "Arrays and Indexes" end with "or programming without arrays? (rather than with arrays)?

Should the last paragraph, on Procedural Programming, be re-expressed to ntot require understanding what constitutes procedural programming? For example, in Analytica, a scalar product might be Sum (A*B, index), whereas in a procedural language there might be a For or While loop.

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