We often have to make decisions here and now, without complete knowledge about problem data or the occurrence of future events. In distribution logistics, significantly uncertain demand must be faced; in finance, several sources of risks affect the return of an investment portfolio. In all of these settings, the future effect of actions is not known for sure. Uncertainty can take several forms. In the simplest case, we may be able to gather past information and use that to generate a set of plausible future scenarios. This is where the standard tools of probability and statistics come into play. They will be the subject and are typically considered the core of any course on QMs. To get gradually acquainted with them, let us consider a few toy problems.
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