Lecture 18 - Simulation and @Risk

Lecture 18 - Simulation and @Risk - Lecture 18 DADSS...

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1 Lecture 18 Simulation with @Risk DADSS
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2 Administrative Details Exam 2 Review Sessions TBA Exam 2 is Thursday, 4/3 7:30pm-8:50pm DH Make-up exam in class that morning Questions from last class?
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3 Limitations of Excel As useful as Excel is for simulation, there are a  number of limitations Number of iterations limited, for most purposes to <  65,536 Selection of distributional forms is limited Output reporting is non-existent (or entirely do-it- yourself) Correlation is very difficult to incorporate @Risk is one of several software products that  facilitates simulation analysis within Excel An additional tool: distribution fitting
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4 Starting up @Risk The Decision Tools Toolbar The @Risk Toolbar
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5 Key Elements Entering Information Syntax Correlations Fitting Distributions Running Simulations Simulation options Examining Output Reporting
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6 Syntax @Risk functions are very similar to Excel functions,  except that they all begin with ‘Risk’ RiskNormal RiskTruncate RiskMean 3 types of @Risk functions Distribution Functions (RiskNormal) Used for adding a variable with a particular distribution to your  model Property Functions (RiskTruncate) Used for modifying the way a variable is sampled, such as  truncating a distribution to produce only numbers within a certain  range Statistics Functions (RiskMean) Used for incorporating the results of a simulation analysis in a  model
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7 Syntax The distribution functions are most  important In general, they take the parameters of  the distribution, and then can optionally  take modification parameters (such as the  property functions) 
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This note was uploaded on 09/20/2010 for the course SDS 88223 taught by Professor Fischbeck during the Spring '10 term at Carnegie Mellon.

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Lecture 18 - Simulation and @Risk - Lecture 18 DADSS...

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