Project Costing with Monte Carlo Simulated Probabilities

Project Costing with Monte Carlo Simulated Probabilities, available at $29.99, has an average rating of 4.5, with 24 lectures, based on 28 reviews, and has 164 subscribers.

You will learn about How to calculate probabilistic contingency using Monte Carlo simulation, considering all kinds of risks on any type of project. The objective is to demonstrate a number of basic and intermediate tools from @RISK that are relevant to current practices used in the world of project management. The goal is to show how @RISK tools can be used to represent quantitative – not qualitative – risk analysis. This course is ideal for individuals who are Project-related professionals and students: Project managers, cost estimators, cost engineers, project planners and schedulers. It is particularly useful for Project-related professionals and students: Project managers, cost estimators, cost engineers, project planners and schedulers.

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Summary

Title: Project Costing with Monte Carlo Simulated Probabilities

Price: $29.99

Average Rating: 4.5

Number of Lectures: 24

Number of Published Lectures: 24

Number of Curriculum Items: 24

Number of Published Curriculum Objects: 24

Original Price: $34.99

Quality Status: approved

Status: Live

What You Will Learn

How to calculate probabilistic contingency using Monte Carlo simulation, considering all kinds of risks on any type of project. The objective is to demonstrate a number of basic and intermediate tools from @RISK that are relevant to current practices used in the world of project management. The goal is to show how @RISK tools can be used to represent quantitative – not qualitative – risk analysis.

Who Should Attend

Project-related professionals and students: Project managers, cost estimators, cost engineers, project planners and schedulers.

Target Audiences

Project-related professionals and students: Project managers, cost estimators, cost engineers, project planners and schedulers.

We present here an integrated business case for calculating a simplified project cost estimation. An integrated case for calculating a simplified project cost and its probabilistic contingency reserve estimation. Quantification of price and quantity risk as well as event risks. The objective of presenting this example is to demonstrate a number of basic and intermediate tools from @RISK that are relevant to current practices used in the world of project management. The goal is to show how @RISK tools can be used to represent quantitative – not qualitative – risk analysis.

Course Curriculum

Chapter 1: Introduction and Defining the Problem

Lecture 1: Introduction to the course

Lecture 2: Using a Probabilistic Approach

Lecture 3: Contingency Reserve Usage

Lecture 4: Considering Event Risks

Chapter 2: Traditional Approaches to Contingency Estimation

Lecture 1: Determining Contingency Reserve With Emv

Chapter 3: Structuring The @RISK Model

Lecture 1: Inserting Variability To Project Activities

Lecture 2: Inserting Variability To Project Activities: Part 2

Lecture 3: Structuring The First Event Risk: Client Breach

Lecture 4: Structuring The Second Event Risk: Subcontractors Going Out Of Business: 1

Lecture 5: Structuring The Second Event Risk: Subcontractors Going Out Of Business. Part 2

Lecture 6: Structuring The Third Event Risk: Weather Related Delays

Lecture 7: Completing Details To Run The First Simulation

Chapter 4: Interpreting Results

Lecture 1: Interpreting Simulation Results: Histogram

Lecture 2: Interpreting Simulation Results: Tornado Graphs

Lecture 3: The Riskmakeinput Function

Lecture 4: Interpreting Tornado: Change In Output Mean

Lecture 5: Interpreting Tornado: Regression Coefficients

Lecture 6: Interpreting Tornado: Scatterplots

Lecture 7: Interpreting Tornado: Correlation Coefficients (Spearman Rank)

Lecture 8: Interpreting Tornado: Regression Mapped Values

Lecture 9: Interpreting Tornado: Contribution To Variance

Lecture 10: Interpreting Tornado: Spider Graph – Change In Output Mean

Chapter 5: Advanced Settings

Lecture 1: Inserting Simulation Statistics

Lecture 2: Inserting Results Graphs

Instructors

Fernando Hernandez
Risk and Decision Analysis Consultant and Trainer

Rating Distribution

1 stars: 0 votes
2 stars: 0 votes
3 stars: 4 votes
4 stars: 15 votes
5 stars: 9 votes

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