• Adding sampled parameters with triangular distribution
• Calculating a probabilistic case
• Plotting results from a probabilistic case

• Stochastic parameters are parameters defined using a Probability Density Function (PDF), rather than a discrete value.
• Deterministic Cases in AMBER are cases in which none of the parameters are defined using PDFs.
• Probabilistic Cases in AMBER are cases in which one or more parameters is sampled
• Full Sampling allows variation over all sampled parameters
• Partial Sampling allows variation over some sampled parameters, and fixes other at their best estimate values
• Best Estimates Sampling fixes all sampled parameters to their best estimates, making the calculation deterministic
• Latin Hypercube Sampling generates a sample set that optimises the coverage when a number of parameters are sampled together
• Seeds are used in probabilistic calculations to initiate the random number generator that determines the sampled values.

This video covers section 9.1 of the User Guide.