The Ultimate Risk Analysis Training and Reference Tool for @RISK
Have
you ever asked yourself:
How do I build a risk analysis model?
Which distributions do I use?
How do I make the best use of data in risk analysis?
How can I construct distributions that are not available in @RISK?
How do I properly fit distributions to data?
How can I validate my model?
The answers to these and many other questions are now available in ModelAssist. Developed by David Vose and his team at Vose Consulting, ModelAssist is by far the most comprehensive risk analysis training and reference tool for @RISK users! With over 500 risk analysis topics, many videos, quizzes and over 140 example models, ModelAssist will unleash the full power of your software and bring you to the next level of quantitative risk analysis.
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A Comprehensive Risk Analysis Database
ModelAssist guides you in how to approach a risk issue, how to perform a technically
correct risk analysis that provides real management insight, and how to present the
findings. ModelAssist is a self-contained training database with
full navigation and search facilities. With ModelAssist you will be able to realise
the full potential of @RISK, and confidently develop accurate, defensible and useful
risk analysis models.
Sixteen Years of Experience
David Vose, principle of Vose Consulting, is the author of the critically acclaimed
book Risk Analysis: A Quantitative Guide, available from Palisade. ModelAssist explains
the techniques that Vose Consulting have actually used in 16 years of real-world
problem solving. ModelAssist will provide you with @RISK specific issues and teach
you the concepts of risk analysis: from problem definition, through model design
and execution, to presenting, interpreting and using the results.
ModelAssist
Basic Edition
Simple modelling techniques and applications for general risk analysis.
ModelAssist
Advanced Edition
A huge range of methods from beginner level to advanced that should allow you to address
a very large number of risk issues.
Tips
from ModelAssist
Estimating
a probability, fraction or prevalence (‘p’)
Incorporating
differences in expert opinion
How
many iterations should I use?



