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
Confidence Intervals and Limits for Projects
The whole point of studying statistics in the context of projects is to make it easier to forecast outcomes and put plans in place to affect those outcomes if they are not acceptable or reinforce outcomes if they present a good opportunity for the project. It often comes down to "confidence" rather than a specific number. Confidence in a statistical sense means "with what probability will the outcome be within a range of values?" Estimating confidence stretches the project-forecasting problem from estimating the probability of a specific value for an outcome to the problem of forecasting an outcome within certain limits of value.
Mathematically, we shift our focus from the PDF to the cumulative probability function. Summing up or integrating the probability distribution over a range of values produces the cumulative probability function. The cumulative probability equals the sum (or integral) of the probability distribution over all possible outcomes.
The "S" Curve
Recall that the cumulative probability accumulates from 0 to 1 regardless of the actual distribution being summed or integrated. We can easily equate the accumulating value as accumulating from 0 to 100%. For example, if we accumulate all the values in a Normal distribution between 1 ? of the mean, we will find 68.3% of the total value of the cumulative total. We can say with 68.3% "confidence" that an outcome from a Normal distribution will fall in the range of 1 ? of the mean; the corollary is that...
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