Probability of Completing a Project: Normal Distribution - Program Evaluation & Review Technique (PERT) and Range Estimating | Coursera

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Probability of Completing a Project: Normal Distribution

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Construction Scheduling

Universidad de Columbia

4.8 (1,141 calificaciones) | 15K estudiantes inscritos

Curso 2 de 4 en Gestión de obras Programa Especializado

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Learners will discover the key project scheduling techniques and procedures including; how to create a network diagram, how to define the importance of the critical path in a project network, and defining project activities float. Also covered are the fundamentals of Bar Charts, Precedence Diagrams, Activity on Arrow, PERT, Range Estimating, and linear project operations and the line of balance.

Destrezas que aprenderás

Schedule, Linear Scheduling Method, Program Evaluation And Review Technique (PERT), Critical Path Method

Revisiones

4.8 (1,141 calificaciones)

5 stars
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LF

May 14, 2020

Sufficient detail (rather than broad concepts) with active, practical learning aspects to it. Easy to navigate and dip in & out as you reference other materials to assist with learning.

GJ

Sep 28, 2019

This course is dedicated to anyone in the construction management industry and/or the willingness to learn about construction management. I will highly recommend this course!

De la lección

Program Evaluation & Review Technique (PERT) and Range Estimating

The Program Evaluation and Review Technique (PERT) is introduced in this module which relates to uncertainty in estimating the duration of construction activities in a project schedule. PERT helps project managers determine the probability of a project being completed in a certain number of days.

Program Evaluation and Review Technique7:53

Probability of Completing a Project: Normal Distribution5:21

PERT Probability Example12:33

PERT Example on Completing a Project10:45

PERT Calculations: Critical Activities16:12

Applying PERT: Range Estimating19:51

Impartido por:

Ibrahim Odeh, Ph.D., MBA
Instructor, Department of Civil Engineering and Engineering Mechanics, Columbia University

Prueba el curso Gratis

Transcripción

So moving forward the probability of completing the project is calculated by assuming that the probability distribution of the total project duration is normal distributed with the longest path, of te, the values, or the expected values as a mean value of the normal distribution. And I will explain further in details with numbers and highlight the curves to understand this definition and the concept of the normal distribution of the entire project. So, the normal distribution is defined by three points here, one is the mean value, or te or x which is the expected value, duration of that entire project. Second, is the standard deviation or sigma here, and the value sigma or standard deviation, this shows how widely about te about the mean value. The actual observed values are spread or distributed, and the equation for that is the following. tb minus ta, tb is the worst case scenario that pessimistic duration of that activity minus the ta which is the optimistic of that activity, optimistic duration divided by 6. That's the standard deviation. Now, the last one is the variance. And the variance is that square of that standard deviation as we can see here. We refer to it as V or the sigma squared. And the summation of the V for all critical activities, not all activities, just the critical activities, you find the variance for all of them, and you sum up all of them, and that is the variance of the entire project duration. Which then we can also calculate the standard deviation of the entire project from the variance of the project. What I mean by that, that you find the variance, which would be exactly the same equation but at the end here in the top, you have the power 2. After you find the values for each of these critical activities, you sum it up and then you take the square root of that number to give you the standard deviation of the project. Now, and we will go through an example soon. Now, mathematically, in normal distribution, it can be shown that 99.7% of the values of normally distributed values or normally distributed variables will lie in a range defined by three standard deviations or three sigma. Below the mean, the te or x here and three standard deviation above the mean or above the te or the x of the project, and as we can see in the figure here. So this is te and this is what we refer to as the normal distribution. It has same distribution from the right of the mean to the left of the mean of te and when you go one signal to the right, one signal to the left on te. The area here, It will be equal to 68.2%. The entire area under the curve is the 100%. So when you go 2 sigma, to the right and to the left, the area, here, until like the 2 sigma. It will cover around 95.4%, and when you go up to 3 sigma on each direction, the area under the curve, it will be closer to 99.7%, or to the 100%.

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