Discrete Probability, Stochastic Processes, and Statistical Inference

Catalog description

The purpose of this course is to provide a 1 CU educational experience which tightly integrates the theory and applications of discrete probability, discrete stochastic processes, and discrete statistical inference in the study of computer science. The intended audience for this class is both those students who are CS majors as well as those intending to be CS majors. Specifically, it will be assumed that the students will know: Set Theory, Mathematical Induction, Number Theory, Functions, Equivalence Relations, Partial-Order Relations, Combinatorics, and Graph Theory at the level currently covered in CIS 1600 . This course could be taken immediately following CIS 1600 . Computation and Programming will play an essential role in this course. The students will be expected to use the Maple programming environment in homework exercises which will include: numerical and symbolic computations, simulations, and graphical displays.