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Decision-Making and Quantitative Risk Analysis using the DecisionTools Suite: Part I & II

05 Sep

Decision-Making & Quantitative Risk Analysis using the DecisionTools Suite: Part I & II
Live Web Training

As part of my preparation to become a successful Project Manager, I’ll be attending Palisade’s Web Training about Decision Making & Quantitative Risk Analysis, using the DecisionTools Suite.I’ll take Part I & II of the Web Trainings to have a complete understanding of the Suite.

I won these trainings after attending their conference in Panama about:

“Quantifying Strategic Risks for Enterprises” (Panama, July 9th, 2012 – Miramar Hotel)

6-7 September 2012, 9:00am – 1:00pm ET (2:00pm – 6:00pm GMT)
Price: $595.00

Part I of our DecisionTools Suite-specific training consists of two 4-hour sessions spread over 2 days. Attendees will discover how to translate their deterministic Excel analysis into an @RISK model that can be used to quantify exposure and test mitigation strategies. This session employs simple examples to present modeling techniques and the capability of the software, as well as simulation analysis. This course provides a sound introduction to @RISK.

Introduction

  1. Overview of Palisade Corporation
  2. Course Overview
  3. Introduction to Risk and Decision Assessment
    1. Concept
    2. Statistics and Probability
    3. Probability Distributions – common functions
      1. Discrete distributions
        1. Bernouli
        2. Binomial
        3. Discrete
        4. Poisson
      2. Continuous distributions
        1. Normal
        2. Lognormal
        3. Triangular
        4. PERT
        5. General
    4. Monte Carlo Simulation
      1. Sampling method
      2. Latin Hypercube
    5. Decision Analysis
      1. Maximum value
      2. Criteria
  4. Developing a Case Study scenario

Viewing Simulation Results Using @RISK

  1. MC Simulation of Simple Model
  2. Viewing Results Summary
  1. Distributions
  2. Statistics
  1. @RISK Reports
  1. Detailed Statistics
  2. Data
  1. @RISK Analyses
  1. Sensitivity
  2. Scenarios
  1. Sharing Simulation Results
  1. Excel Reports
  2. Stats Functions, etc.
  3. @RISK Library
  1. Sharing Model Information
  1. Swap Function
  2. RiskTemplate
  1. Additional @RISK Features
  2. Advanced Analyses

Decision-Making & Quantitative Risk Analysis using the DecisionTools Suite: Part II
Live Web Training

Date: 17-18 December 2012, 11:00am – 3:00pm ET (8:00am – 12:00pm PT):
Price: $595.00
Part II of our DecisionTools Suite Live Web training consists of two 4-hour sessions spread over 2 days. Materials presented in Part II build upon those presented in Part I. Therefore, it is highly recommended that registrants have completed the Part I course or demonstrate a strong working knowledge and experience with the DecisionTools Suite.Refining the model:
Correlation and Interdependence

  1. Correlating Risk Inputs
    1. Impact
    2. Simple Calculation Example
  2. Correlation Methodology
    1. Pearson
    2. Rank
    3. Application
  3. Time Dependent Risk
    1. Impact
    2. Application
    3. Time Series Correlation

Selecting Distributions

  1. Introduction
  2. Expanded Distribution Selection
    1. Bootstrap Method
  3. Distribution Fitting
    1. Interface
    2. Fit Manager
    3. Linking Data
  4. Expert Opinion
    1. Alternate Parameters
    2. Judgment and Bias
  5. @RISK Library

Building a Decision Tree Using PrecisionTree

  1. Laying out options for the case study model
  2. Simple analysis of outcomes
    1. Interpreting tree results
      1. Calculation method
      2. Value assessment
    2. Risk Profile
      1. Statistics
    3. Policy Suggestion
  3. Sensitivity Analysis
    1. One-Way
    2. Two-Way
  4. Assessment

Building a Scenario Analysis Model
Using TopRank

  1. Structuring the Excel model
  2. Defining What-If parameters
    1. Analysis Settings
    2. Adding Outputs
  3. What-If Sensitivity Analysis
    1. Reports
    2. Detail
  4. Assessment

Evolving An Optimal Solution
Using RISKOptimizer

  1. Introduction to optimization
    1. Genetic algorithm
    2. Adjustable cells
    3. Variables
    4. Constraints
    5. Solving methods
    6. Reports and solution
  2. Application to case study
  3. Assessing variation of optimal solution
    1. Applying @RISK to optimized results
    2. Analysis of simulation
    3. Reporting capabilities revisited

Additional Features

  1. Multiple simulations (@RISK)
    1. Simtable
    2. Scenarios
  2. Advanced Analyses (@RISK)
    1. Stress
    2. Advanced Sensitivity
  3. Other Solving methods (RISKOptimizer)
  4. Influence Diagrams (PrecisionTree)
  5. Simulating decision trees (PrecisionTree & @RISK)

Statistical Analysis

  1. Statistical Analysis interface (StatTools)
    1. Data Analysis
    2. Reporting capabilities
    3. Highlight basic statistical functions

Predicting Outcomes
Using NeuralTools

  1. Defining a model
  2. Train
  3. Test
  4. Predict

Review of Additional Example Models

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Posted by on 5 de September de 2012 in Information Technology

 

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