Ebook: Quantitative methods for project management
Author: Anbari F.
- Genre: Business // Management: Project Management
- Tags: Менеджмент, Управление проектами
- Language: English
- pdf
Frank T Anbari, International Institute for Learning, 1997, 64 pages.Preface:
This booklet provides the reader with a summary of selected quantative methods procedures. These procedures are selected in view of their wide applicability in project management. The aim of this booklet is to facilitate the understanding of the mechanics of these procedures and their underlying theory.As a result, it is anticipated that the reader will be able to devote more time and effort to understanding the theories behind these procedures and expanding their applications to their own projects. There is no substitute for profound knowledge of quantitive method tools. Such knowledge is imperative for excellence in project management.Table of contents:
Populations, Processes and Samples.
Descriptive Statistics.
Probability.
Probability Distributions.
Sampling and Sampling Distribution.
Decision Theory and the Expected Value.
Probability Trees and Decision Trees.
Quality Management Tools.
Control Charts.
Process Capability.
Acceptance Sampling.
Utility Theory.
Forecasting and Simulation.
Depreciation.
Capital Budgeting.
Break-even Analysis.
Earned Value Analysis.
References.
This booklet provides the reader with a summary of selected quantative methods procedures. These procedures are selected in view of their wide applicability in project management. The aim of this booklet is to facilitate the understanding of the mechanics of these procedures and their underlying theory.As a result, it is anticipated that the reader will be able to devote more time and effort to understanding the theories behind these procedures and expanding their applications to their own projects. There is no substitute for profound knowledge of quantitive method tools. Such knowledge is imperative for excellence in project management.Table of contents:
Populations, Processes and Samples.
Descriptive Statistics.
Probability.
Probability Distributions.
Sampling and Sampling Distribution.
Decision Theory and the Expected Value.
Probability Trees and Decision Trees.
Quality Management Tools.
Control Charts.
Process Capability.
Acceptance Sampling.
Utility Theory.
Forecasting and Simulation.
Depreciation.
Capital Budgeting.
Break-even Analysis.
Earned Value Analysis.
References.
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