Applied Probability

This is a first course in the sense that it presumes no previous course in probability. The units are numbered as they appear in the text although of course they may be used in any desired order. For those who wish to use the order of the text an outline is provided with indication of which modules contain the material.The mathematical prerequisites are ordinary calculus and the elements of matrix algebra. A few standard series and integrals are used and double integrals are evaluated as iterated integrals. The reader who can evaluate simple integrals can learn quickly from the examples how to deal with the iterated integrals used in the theory of expectation and conditional expectation. Appendix B (Section 17.2) provides a convenient compendium of mathematical facts used frequently in this work. And the symbolic toolbox implementing MAPLE may be used to evaluate integrals if desired. In addition to an introduction to the essential features of basic probability in terms of a precise mathematical model the work describes and employs user dened MATLAB procedures and functions (which we refer to as m-programs or simply programs) to solve many important problems in basic probability. This should make the work useful as a stand alone exposition as well as a supplement to any of several current textbooks.Most of the programs developed here were written in earlier versions of MATLAB but have been revised slightly to make them quite compatible with MATLAB 7. In a few cases alternate implementations are available in the Statistics Toolbox but are implemented here directly from the basic MATLAB program so that students need only that program (and the symbolic mathematics toolbox if they desire its aid in evaluating integrals). Since machine methods require precise formulation of problems in appropriate mathematical form it is necessary to provide some supplementary analytical material principally the so-called minterm analysis. This material is not only important for computational purposes but is also useful in displaying some of the structure of the relationships among events.