Difference between revisions of "If you don’t read manuals"

Latest revision as of 01:32, 18 October 2017

Analytica User GuideIntroduction: About AnalyticaIf you don’t read manuals

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.

@@ Line 7: / Line 7: @@
 find especially helpful to review.
-{| class="wikitable"
+:{| class="wikitable"
 !Chapter
 !Contents
 |-
 | [[Building Effective Models]]
-|Offers guidelines for creating effective models, distilled from the experience of master modelers. It offers a practical guide for building effective 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.
+|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 Influence Diagrams|Creating Lucid Diagrams]]
-|Gives tips on how to create influence diagrams that are truly lucid and elegant — and how to avoid incomprehensible spaghetti.
+|Tips on how to avoid producing incomprehensible spaghetti -- and create influence diagrams that are truly lucid and even elegant.
 |-
 |[[Arrays and Indexes]]
-|Explains Analytica’s Intelligent Arrays™. After you grasp the essentials, they let you build complex multidimensional models with surprising ease. But, 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. We recommend that even — perhaps especially — experienced modelers review this chapter.
+|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]]
-|Discusses 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 controlling and displaying probabilistic values.
+|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]]
-|With Analytica, you can create large and sophisticated models without procedural programming. But, if you really want to write complex procedural functions, read this chapter to understand Analytica as a programming language.
+|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==
+* [[Analytica Tutorial]]
+* [[Creating Lucid Influence Diagrams]]
+* [[Building Effective Models]]
+* [[Arrays and Indexes]]
+* [[Expressing Uncertainty]]
+* [[Procedural Programming]]
 <footer>Welcome! / {{PAGENAME}} /Hardware and software requirements</footer>