Triangular Distribution
Where do you meet this distribution?
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Project management -- PERT, CPM and so on
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Digital signal processing (dithering) -- digital audio, digital video, digital photography, seismology, RADAR, weather forecasting systems and many more
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Data security
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Business simulation (Corporate finance)
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Proxy of Beta distribution
Shape of Distribution
Basic Properties
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Three parameters are required (How can you get these).
These parameters are minimum value of variable, maximum value of variable and mode of the distribution respectively.
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Continuous distribution defined on bounded range
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This distribution can be symmetric or asymmetric.
Probability
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Cumulative distribution function
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How to compute these on Excel.
A | B | |
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1 | Data | Description |
2 | 1.5 | Value for which you want the distribution |
3 | 1 | Value of parameter Min |
4 | 3 | Value of parameter Max |
5 | 1.4 | Value of parameter Mode |
6 | Formula | Description (Result) |
7 | =NTTRIANGULARDIST(A2,A3,A4,A5,TRUE) | Cumulative distribution function for the terms above |
8 | =NTTRIANGULARDIST(A2,A3,A4,A5,FALSE) | Probability density function for the terms above |
- Function reference : NTTRIANGULARDIST
Quantile
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Inverse function of cumulative distribution function
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How to compute this on Excel.
A | B | |
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1 | Data | Description |
2 | 0.5 | Probability associated with the distribution |
3 | 1 | Value of parameter Min |
4 | 3 | Value of parameter Max |
5 | 1.4 | Value of parameter Mode |
6 | Formula | Description (Result) |
7 | =NTTRIANGULARINV(A2,A3,A4,A5) | Inverse of the cumulative distribution function for the terms above |
- Function reference : NTTRIANGULARINV
Characteristics
Mean - Where is the `center'' of the distribution? (Definition)
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Mean of the distribution is given as
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How to compute this on Excel
A | B | |
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1 | Data | Description |
2 | 1 | Value of parameter Min |
3 | 3 | Value of parameter Max |
4 | 1.4 | Value of parameter Mode |
5 | Formula | Description (Result) |
6 | =NTTRIANGULARMEAN(A2,A3,A4) | Mean of the distribution for the terms above |
- Function reference : NTTRIANGULARMEAN
Standard Deviation -- How wide does the distribution spread? (Definition)
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Variance of the distribution is given as
Standard Deviation is a positive square root of Variance.
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How to compute this on Excel
A | B | |
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1 | Data | Description |
2 | 1 | Value of parameter Min |
3 | 3 | Value of parameter Max |
4 | 1.4 | Value of parameter Mode |
5 | Formula | Description (Result) |
6 | =NTTRIANGULARSTDEV(A2,A3,A4) | Standard deviation of the distribution for the terms above |
- Function reference : NTTRIANGULARSTDEV
Skewness -- Which side is the distribution distorted into? (Definition)
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Skewness of the distribution is given as
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How to compute this on Excel
A | B | |
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1 | Data | Description |
2 | 1 | Value of parameter Min |
3 | 3 | Value of parameter Max |
4 | 1.4 | Value of parameter Mode |
5 | Formula | Description (Result) |
6 | =NTTRIANGULARSKEW(A2,A3,A4) | Skewness of the distribution for the terms above |
- Function reference : NTTRIANGULARSKEW
Kurtosis -- Sharp or Dull, consequently Fat Tail or Thin Tail (Definition)
- Kurtosis is .
Random Numbers
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Random number x is generated by inverse function method, which is for uniform random U,
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How to generate random numbers on Excel.
A | B | |
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1 | Data | Description |
2 | 0 | Value of parameter A |
3 | 3 | Value of parameter B |
4 | 1.8 | Value of parameter C |
5 | Formula | Description (Result) |
6 | =NTRANDTRIANGULAR(100,A2,A3,A5,0) | 100 triangular deviates based on Mersenne-Twister algorithm for which the parameters above |
Note The formula in the example must be entered as an array formula. After copying the example to a blank worksheet, select the range A6:A105 starting with the formula cell. Press F2, and then press CTRL+SHIFT+ENTER.
NtRand Functions
- If you already have parameters of the distribution
- Generating random numbers based on Mersenne Twister algorithm: NTRANDTRIANGULAR
- Computing probability : NTTRIANGULARDIST
- Computing quantile : NTTRIANGULARINV
- Computing mean : NTTRIANGULARMEAN
- Computing standard deviation : NTTRIANGULARSTDEV
- Computing skewness : NTTRIANGULARSKEW
- Computing kurtosis : NTTRIANGULARKURT
- Computing moments above at once : NTTRIANGULARMOM
- If you know mean, standard deviation and mode of the distribution
- Estimating parameters of the distribution:NTTRIANGULARPARAM