Quantitative Methods in Project Management
This book combines theoretical and practical applications and takes project managers through the most important quantitative methods, integrates them, and illustrates interrelationships.
TABLE OF CONTENTS Quantitative Methods in Project Management
Key Statistics Used in Projects
Strictly speaking, statistics are data. The data need not be a result of analysis. Statistics are any collection of data. We often hear, "What are the statistics on that event?" In other words, what are the numbers that are meaningful for understanding? Perhaps the most useful definition of statistics is that statistics is the "methods and techniques whereby collections of data are analyzed to obtain understanding and knowledge." [13] Statistical methods are by and large methods of approximation and estimation. As such, statistical methods fit very well with project management since the methods of project management are often approximate and based only on estimates.
Informational data, of course, are quite useful to project managers and to members of the project management team for estimating and forecasting, measuring progress, assessing value earned, quantifying risk, and calculating other numerical phenomena of importance to the project. Statistical methods provide some of the tools for reducing such data to meaningful information which the team uses to make decisions.
Expected Value and Average
The best-known statistic familiar to everyone is "average" (more properly, arithmetic average), which is arithmetically equal to a specific case of expected value. Expected value, E, is the most important statistic for project managers. The idea of expected value is as follows: In the face of uncertainty about a random variable that has values over a range, "expected value" [14] is the "best" single number to represent a range of estimated value of that...
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