# 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.

### Expected value

**expectationexpectedmean**

The mean (expected value) is then:

### 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):

### List of statistics articles

**list of statistical topicslist of statistics topics**

Three-point estimation