Abstract
In earth sciences, there are regular data sets as time series and irregular data sets in the forms of uncontrollable variable measurements such as floods, droughts, earthquake occurrences, volcanic eruptions, stratigraphic thicknesses, fractures, fissures, or ore content. The uncertainty features in both data sets require probabilistic and statistical data processing techniques, which are the main topics of this chapter. For this purpose, prior to any methodology, the empirical frequency definition of various types is given, and their connections with the probability theory are explained with examples. Subsequently, probabilistic and statistical prediction modeling tools are presented for independent and dependent processes.