20425 Probability for Computer Science Students 1

Credits: 4 intermediate credits in Mathematics

Prerequisites: none

Required: One of the following: Infinitesimal Calculus I, Differential and Integral Calculus I

This course is an abridged version of Probability Theory (20416) that covers the topics required for Computer Science studies. Like Probability Theory, it was developed by Abraham Ginzburg, Yossi Kaufman and Naomi Milano-Rosenthal, based on a translation of chapters 1-8 of A First Course in Probability (5th ed.), by S. Ross (Prentice Hall, 1998).

Topics: Combinatorial analysis; Axioms of probability; Conditional probability and independence; Random variables; Continuous random variables (normal, exponential and uniform); Jointly distributed random variables (discrete); Properties of expectation; Limit theorems.

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1There is some overlap in the content of this and other courses. For details, see Overlapping Courses.