eldo_user

Monte Carlo Analysis
Additional Uncertainty Analyses (the .mcm File)
• The inter-quartile range is the value of the 75th percentile minus the value of the 25th
percentile. This measure of dispersion attempts to measure the variability of points near
the center.
The inter-quartile range is an estimates of dispersion that have robustness of type I (but not of
type II).
Note
If the histogram of an output measure indicates that the data are in fact reasonably
approximated by a normal distribution, then it makes sense to use the standard deviation as
the estimate of dispersion. However, if the data are not normal, and in particular if there are long
tails, then using an alternative measure such as inter-quartile range makes sense. Moreover,
comparing the range to the standard deviation gives an indication of the spread of the data in the
tails.
Min/Max Values
Minimum and maximum values in data sample are given for each output measures in the
following table.
==> Min and Max Values:
Min ... Minimum Value Max ... Maximum Value
I-min ... Index of Minimum I-max ... Index of Maximum
Index
Name
of Meas I-min Min I-max Max Range of Meas
--------------------------------------------------------------------------------
1 231 7.12613e-01 367 9.85080e-01 2.72468e-01 MAX
2 551 2.13597e+00 247 2.26746e+00 1.31492e-01 BW
3 109 -5.68030e-02 711 -5.21231e-02 4.67989e-03 IVDD
We also provide the index of the corresponding run. These numbers may be used with the IRUN
argument on the .MC command for extracting more informations of these “extreme”
simulations.
Parametric Fit and Normality Test
The section “Parametric Fit and Normality Test” in the .mcm file is important when the designer
wants to check the normality assumption of the sample data.
Scale and Shape
We provide the sample estimates of the third and fourth standardized moments as an indication
of non-normality.
These two standardized moments of interest are given by:
Eldo® User's Manual, 15.3 495