Rocscience International Conference 2025 is going to take place in Sydney, Australia Read more

Search Results

Statistical Distributions Overview

Each Random Variable that you define for a Slide2 Probabilistic Analysis, must have a Statistical Distribution selected. The following Statistical Distributions are available in Slide2:

The type of Statistical Distribution, together with the statistical parameters of the distribution (mean, standard deviation, minimum and maximum values), defines a "probability density function" for the Random Variable. A "probability density function" is commonly referred to as a PDF.

The PDF describes the distribution of possible values that the Random Variable may assume, for a hypothetical, infinite set of observations of the variable.

In most cases, very limited data is available, on which to decide what Statistical Distribution and standard deviation to use. Therefore, the engineer must often rely on "best estimates", when defining the PDF for a Random Variable.

Normal Distribution

A Normal Distribution is commonly used for statistical analysis in geotechnical engineering. When the true distribution of a variable is not known, a Normal Distribution is often assumed. By making a best estimate of the minimum and maximum values of the variable, a standard deviation can be estimated. This is described in the Normal Distribution topic.

Other Distributions

Although a Normal Distribution is most commonly used, the user should become familiar with the properties, and advantages of using other Statistical Distributions.

  • For example, variables which can only have positive values (such as Cohesion, for example), often have PDFs which are NOT well modelled by a Normal Distribution. Such variables may have non-symmetric distributions, with a peak in the distribution at low values, and a gradual tapering off at higher values. For such variables, it is often more appropriate to use a Lognormal or Gamma distribution, rather than a Normal distribution.
  • Other variables may be best modelled with an Exponential distribution. For example, the level of a Water Table might be modelled using an Exponential Distribution, if high Water Tables are expected only rarely, due to infrequent rainfall.
  • A Uniform Distribution can be useful, if you wish to specify an equal probability of the variable, taking on any value between the minimum and maximum values.

The Statistical Distributions available in Slide2 are briefly described in the following topics. For further information, you should consult one of the many reference works which are available on the subject.

Rocscience logo, click here to return to the homepage Portal Account Portal Account Log In Log Out Home Shopping Cart icon Click here to search our site Click here to close Learning Tech Support Documentation Info Chevron Delete Back to Top View More" Previous Next PDF File Calendar Location Language Fees Video Click here to visit Rocscience's LinkedIn page Click here to visit Rocscience's YouTube page Click here to visit Rocscience's X page Click here to visit Rocscience's Facebook page Click here to visit Rocscience's Instagram page Click here to visit Rocscience's Reddit page Bookmark Network Scroll down for more Checkmark Download Print Back to top Single User Multiple Users RSLog RocFall3 CPillar Dips EX3 RocFall RocPlane RocSlope3 RocSupport RocTopple RS2 RS3 RSData RSPile Settle3 Slide2 Slide3 SWedge UnWedge RocTunnel3 RocSlope2 BlastMetrix ShapeMetriX Fragmenter Commercial License Education License Trial License Shop safe & secure Money-back guarantee