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This Concept Map, created with IHMC CmapTools, has information related to: Chapter 2 - P Richardson, t ∈ T, X(t) when T is an interval it is called a continuous time process, Random Variables can be Discrete, Geometric and Poisson, Discrete or Continuous, Bernoulli and Binomial, Uniform and Exponential, Gamma and Normal, Continuous which include Uniform, Random Variables deal with the function of the outcome rather than the outcome itself, stochastic process sometimes denoted as t ∈ T, X(t), Binomial and Geometric, stochastic process in which t stands for time whereas X(t) is the state of the process at time t, Random Variables a collection of which is called a stochastic process, Discrete such as Bernoulli, t ∈ T, X(t) where T is called the index set of the process, t ∈ T, X(t) when T is countable it is said to be Discrete time process, Exponential and Gamma