PMGT589 – Project Risk Management Assignment 2 – Group 5

PMGT5891 Project Risk Management

Assignment 2 – Group 5
Name: Felipe Arcila Eric Jonathan Ernst Bodamer Xintao Hou Minjie Shi Vagi William Student ID: 420160957 420177232 420149985 309108152 430154654

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PMGT589 – Project Risk Management 6/15/2013

PMGT589 – Project Risk Management Assignment 2 – Group 5

Table of Contents
1. 2. 3. 4. 5. 6. 7. Activity 1 – PERT Model ..................................................................................................... 2 Activity 2 – Monte Carlo Model ......................................................................................... 4 Activity 3 – Decision Tree Model…show more content… From this it is advised to consider a new estimate of 118 days. Using the normal distribution function in Excel the probability of the project being achieved in 2 standard deviations from the mean for both the normal and alternative PERT durations is 97.7%.

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PMGT589 – Project Risk Management Assignment 2 – Group 5

2. Activity 2 – Monte Carlo Model
In activity 2, the Monte Carlo method is used to simulate the data generation process and provide a prediction of the expected budget for the GLE case. In order to make sure we will have the most accurate results through this simulation, we have iterated for 100, 1000 and 5000 times for this part. The reason for increased iteration is because the law of large numbers. According to Durrett (2010), the more iteration you have in sample generation, the less deviation between this sample mean and the population mean. In order to conduct this simulation, we will use the “rand()” function in excel. A detailed step-bystep method is provided below. 1. For each of the cost item, we firstly identify the range of this cost based on the minimum and maximum estimation. 2. The number in our simulation is generated though using the difference between the maximum number and minimum number times the “rand()” function and then add the minimum number. Thus, a number within the range will be randomly generated. 3. Lastly, we use the