There are lots of models, and all of them falls into several main categories. Thus, the system we analyze could demonstrate either deterministic or stochastic (in other words, probabilistic) behavior. Therefore, the model that is built on the parameters of one of such systems can be used to process either random effects and elements of chance (which usually are features of a stochastic system) or deal with strict dependence on the initial conditions (which is an obligatory part of the behavior of a deterministic system). The next piece that is important for a Computational Science homework help is whether we can classify the model as dynamic or static. The first has many in common with an animated cartoon where time, conditions and/or characteristics of modeled objects change; the latest model is similar to a map or a snapshot. Usually, models can include combinations of static and dynamic components. At last but not at least, we can evaluate the model either as continuous (time changes smoothly and continuously) or discrete (there are incremental steps in how time changes).