Three-point estimation

The three-point estimation technique is used in management and information systems applications for the construction of an approximate probability distribution representing the outcome of future events, based on very limited information.wikipedia
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Triangular distribution

triangularright-triangle distributionTriangular Probability Density Function
While the distribution used for the approximation might be a normal distribution, this is not always so and, for example a triangular distribution might be used, depending on the application.
Three-point estimation

Five-number summary

five-number summaries
Five-number summary
Three-point estimation

Seven-number summary

Bowley's seven-figure summaryseven-figure summary
Seven-number summary
Three-point estimation

Information system

information systemscomputer information systemssystems
The three-point estimation technique is used in management and information systems applications for the construction of an approximate probability distribution representing the outcome of future events, based on very limited information.

Probability distribution

distributioncontinuous probability distributiondiscrete probability distribution
The three-point estimation technique is used in management and information systems applications for the construction of an approximate probability distribution representing the outcome of future events, based on very limited information.

Normal distribution

normally distributednormalGaussian
While the distribution used for the approximation might be a normal distribution, this is not always so and, for example a triangular distribution might be used, depending on the application.

Mean

mean valuepopulation meanaverage
These are then combined to yield either a full probability distribution, for later combination with distributions obtained similarly for other variables, or summary descriptors of the distribution, such as the mean, standard deviation or percentage points of the distribution.

Standard deviation

standard deviationssample standard deviationsigma
These are then combined to yield either a full probability distribution, for later combination with distributions obtained similarly for other variables, or summary descriptors of the distribution, such as the mean, standard deviation or percentage points of the distribution. These values are used to calculate an E value for the estimate and a standard deviation (SD) as L-estimators, where:

Percentile

percentiles50th percentile85th percentile speed
These are then combined to yield either a full probability distribution, for later combination with distributions obtained similarly for other variables, or summary descriptors of the distribution, such as the mean, standard deviation or percentage points of the distribution.

L-estimator

L-estimation
These values are used to calculate an E value for the estimate and a standard deviation (SD) as L-estimators, where:

Weighted arithmetic mean

averageaverage ratingweighted average
E is a weighted average which takes into account both the most optimistic and most pessimistic estimates provided.

PERT distribution

In Project Evaluation and Review Techniques (PERT) the three values are used to fit a PERT distribution for Monte Carlo simulations.

Monte Carlo method

Monte CarloMonte Carlo simulationMonte Carlo simulations
In Project Evaluation and Review Techniques (PERT) the three values are used to fit a PERT distribution for Monte Carlo simulations.

Confidence interval

confidence intervalsconfidence levelconfidence
The E and SE values are then used to convert the project time estimates to confidence intervals as follows:

Asymptotic distribution

asymptotically normalasymptotic normalitylimiting distribution
These confidence interval estimates assume that the data from all of the tasks combine to be approximately normal (see asymptotic normality).

Work breakdown structure

WBSterminal elementsbreaking down
Decomposes the project into a list of estimable tasks, i.e. a work breakdown structure

Standard error

SEstandard errorsstandard error of the mean
Estimates the expected value E(task) and the standard error SE(task) of this estimate for each task time

Correlation and dependence

correlationcorrelatedcorrelate
Calculates the value SE(project) for the standard error of the estimated total project work time as: under the assumption that the project work time estimates are uncorrelated

Program evaluation and review technique

PERTactivity on arrowCPM/PERT
In Project Evaluation and Review Techniques (PERT) the three values are used to fit a PERT distribution for Monte Carlo simulations.

Project management triangle

bottom up estimateson trackproject triangle
2) Tools: Expert judgment collection, analogous estimating, parametric estimating, Bottom up Estimation, Two-Point estimation, Three-point estimation, reserve analysis

Beta distribution

betabeta of the first kindBeta PDF
The above estimate for the mean is known as the PERT three-point estimation and it is exact for either of the following values of β (for arbitrary α within these ranges):