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This page contains computer files and source code (Excel, DPL, YAAHP, Python scripts, Jupyter notebooks, etc) that are covered in the Decision Analysis classes.

DecisionAnalysisPy Python Module

This Python Module contains all the Class and Function definitions used by all the Python code and Jupyter notebooks covered in class.

 

How to use:

1. Download the Latest Source Code.
2. Unzip the file and copy DecisionAnalysisPy.py to the working directory or folder where you save and execute your .py or .ipynb files.
3. Use apporpiate import statements in your code to access the names in the module you want to use.
4. No pip or conda install needed.
5. See User Guide for documentation and examples from the lecture notes.

Chapter 2: Probabilistic Thinking

Python Code and Jupyter Notebooks

• Do not require DecisionAnalysisPy
• 2.3.2 Plot Posttest probability vs Pretest probability

Excel Files

• 2.1.5 Probability Tree Flipping Excel Templates
  

DPL Models

• 2.2 DPL file for Monty Hall Problem - Decision after choosing door A
• 2.2 DPL file for Monty Hall Problem - Decision after choosing any door initially
• Problem 2.3: DPL file for Monty Hall Problem with Unequal Prior Probabilities

Chapter 4: Basic Decision Analysis

Python Code and Jupyter Notebooks

• Require DecisionAnalysisPy
• 4.3 Party Problem: Plot Risk Profiles using RiskDeal Class
• 4.7 Party Problem: Stochastic Dominance Analysis using RiskDeal Class

 

• Not required
• 4.2.9 Party Problem: Fitting an equation to Kim's utility function
• 4.7 Party Problem: Stochastic Dominance Analysis

Excel Files

• 4.8.1 Kim's Party Problem with Treeplan (Complete analysis with Base model, Sensitivity Analysis, Value of Perfect and Imperfect Information Analysis)
• 4.8.1 Kim's Party Problem with Dynamic Sensitivity Analysis with Treeplan
• 4.8.1 Jane's Party Problem with Treeplan (Complete analysis with Base model, Sensitivity Analysis, Value of Perfect and Imperfect Information Analysis)
• 4.8.2 Kim Party Problem with Precision Tree (Base Model, Risk Profiles, Sensitivity Analysis)

Chapters 5: Influence Diagrams

DPL Models

• 5.3 Kim's Party Problem - DPL Models only
• 5.3 Kim's Party Problem - DPL Models with Outputs

Chapter 6: Advanced Decision Analysis - Risk Preferences

Python Code and Jupyter Notebooks

• Require DecisionAnalysisPy
• 6.1.2 Compute Selling Price under General Risk Preference using RiskDeal Class
• 6.1.3 Compute Buying Price under General Risk Preference using RiskDeal Class
• 6.2.4 Demo Selling Price is Independent of Wealth under Delta Property using RiskDeal Class
• 6.2.5 Demo Buying Price = Selling Price under Delta Property using RiskDeal Class
• 6.2.5 Compute Kim's PISP and PIBP for the Coin Tossing Game using RiskDeal Class
• 6.3.1 Plot Kim's Utility Function using ExpUtilityFunction Class
• 6.3.2 Plot Exponential Utility Functions using ExpUtilityFunction Class
• 6.3.3 Compute Risk Tolerance using 50-50 CE method with ExpUtilityFunction Class

 

• Not Required
• 6.1.3 Compute Buying and Selling Prices using root function
• 6.3.3 Compute Risk Tolerance using 5050-CE method with root function
• 6.5.1 Compute NPV of multi-period cash flows using numpy_financial package

Excel Files

• 6.1.3 Compute Buying and Selling Price using Excel Goal Seek
• 6.3.3 Finding Risk Tolerance using 50-50 CE method with Excel Goal Seek
• 6.5.1 NPV of cash flows
• 6.5.2 Utility of NPV with Treeplan

DPL Models

• 6.1.2 Compute Selling Price using DPL Rainbow Diagram
• 6.1.3 Compute Buying Price using DPL Rainbow Diagram
• 6.5.2 Utility of NPV in DPL version 1 (Using arrays of cash flows and NPV function in DPL)
• 6.5.2 Utility of NPV in DPL version 2 (Using local discounted get/pay cashflows along tree branches)

Chapter 7: Probability Distribution Assessment

Python Code and Jupyter Notebooks

• Require DecisionAnalysisPy
• 7.4.3 Fit Continuous Distributuions to Data using DistFit_continuous Class
• 7.4.3 Fit Discrete Distributuions to Data using DistFit_DistFit Class
• 7.4.4 Fit Normal Distributions with 2 known percentile values using norm_2p Class
• Problem 7.1: Fit distribution using DistFit_continuous Class
• Problem 7.4: Fit distribution using DistFit_continuous Class
• Problem 7.5: Fit distribution using DistFit_continuous Class
• Problem 7.6: Fit distribution using DistFit_discrete Class

 

• Not Required
• 7.2.3 Fit distribution to expert's CDF
• 7.4.3 Fit Continuous Distributions to Data
• 7.4.3 Fit Discrete Distributions to Data
• 7.4.4 Fit Normal Distributions with 2 know percentile values
• 7.4.4 Fit Normal Distributions with known mean and 1 percentile value

Excel Data Files for Exercise Problems

• Data File for Problems P7.1, P7.4, P7.5 & P7.6

Chapter 8: Solving Complex Problems - The DA Process/Cycle

Python Code and Jupyter Notebooks

• Require DecisionAnalysisPy
• 8.2.2 Exxoff Case Study: One-Way Range Sensitivity using OneWayRangeSensit Class
• 8.2.2 Exxoff Case Study: Fit and Discretize Probability Distributions using norm_2p Class
• 8.2.2 Exxoff Case Study: Stochastic Dominance Analysis using RiskDeal Class
• 8.4.2 Lim Case Study: One-Way Range Sensitivity using OneWayRangeSensit Class
• 8.4.2 LIM Case Study: Stochastic Dominance Analysis using RiskDeal Class

 

• Not Required
• Coming soon

DPL Models

• 8.3.1 Exxoff Case Study - DPL file with Models and Outputs
• 8.3.1 Exxoff Case Study - DPL file with Models only (lean and clean)
• 8.4.4 LIM Case Study - DPL file with Models and Outputs
• 8.4.4 LIM Case Study - DPL file with Models only (lean and clean)
• Exercise: Biotecno Problem - DPL file with Models and Outputs
• Exercise: Biotecno Problem - DPL file with Models only (lean and clean)

Chapter 9: MCDM I - Analytic Hierrchy Process

Python Code and Jupyter Notebooks

• Require DecisionAnalysisPy
• 9.2.x Compute AHP matrix using AHPmatrix Class
• 9.4.3 Job Selection Problem: Solution with Sensitivity Analysis using AHP3Lmodel Class
• 9.4.3 Job Selection Problem: Solution with Sensitivity Analysis using AHP4Lmodel Class
• 9.5 Job Selection Problem with SubCriteria: Solution with Sensitivity Analysis using AHP4Lmodel Class
• 9.6.5 Employees Evaluation: AHP Ratings method using AHPratings_model Class
• Problem 9.1: Computer Selection Problem
• Problem 9.2: John and Bill performance rating problem
• Problem 9.3: Investment decision rank reversal problem

 

• Not Required
• 9.2.6 Compute AHP matrix using Linear Algerba method
• 9.2.6 Compute AHP matrix using np.linalg.eig_function
• 9.2.7 Compute AHP matrix using Row Geometric Means Approximation method
• 9.2.7 Compute AHP matrix using Column Normalization Approximation method
• 9.2.8 Compute AHP matrix using Power Iterations method

Excel Files

• Use only Excel worksheet functions
• 9.2.6 Compute AHP Matrix using Linear Algebra method templates
• 9.2.7 Compute AHP Matrix using Row Geometric Means Approximation method templates
• 9.2.7 Compute AHP Matrix using Columns Normalization Approximation method templates

 

• Use VBA user defined functions
• 9.2.x_Compute AHP Matrix using User Defined Functions (All Methods)
• 9.4.2 Job Selection Problem with Sensitivity Analysis using UDF AHPmat_algebra
• 9.4.2 Job Selection Problem with Sensitivity Analysis using UDF AHPmat_power
• 9.5 Job Selection Problem with SubcCriteria Sensitivity Analysis using UDF AHPmat_algebra
• 9.5 Job Selection Problem with SubcCriteria Sensitivity Analysis using UDF AHPmat_power
• 9.6.2 AHP Rating Method with Sensitivity: Employees Evaluation using UDF AHPmat_power
• 9.6.2 AHP Rating Method with Sensitivity: Employees Evaluation using UDF AHPmat_algebra

YAAHP Models

• 9.4 YAAHP file for Job Selection Problem
• 9.5 YAAHP file for Job Selection Problem with Sub-Criteria

Chapter 10: MCDM II - Multiple Attribute Decision Analysis

Python Code and Jupyter Notebooks

• Require DecisionAnalysisPy
• 10.3 Center Relocation Problem: AHP model only using AHP4Lmodel Class
• 10.3 Center Relocation Problem: Complete solutions using AHP4Lmodel Class and Cost_Effective_Analysis Class
• Problem 10.4: Complete AHP and Cost Effectiveness Analysis solutions

Excel Files

• 10.3 Drug Counseling Center Relocation Problem using UDF AHPmat_power
• 10.3 Drug Counseling Center Relocation Problem using UDF AHPmat_algebra

DPL Models

• 10.1.3 DPL file for MAUT Example 1 (Adveristing Campaign Decision)
• 10.1.3 DPL file for MAUT Example 2 (Lisa's Holiday Problem)

YAAHP Models

• 10.3 YAAHP file for Drug Counceling Center Relocation Problem

Chapter 11: Options Thinking in Decision Analysis

DPL Models

• 11.3.2 DPL file for Kim's Party Problem with Options
• 11.4 DPL file for iDesign.com Case Study