Discrete Mathematics for Computer Science

Chapter Review 541

the sum of their expectations. We concluded by discussing how likely it is that the average
of a set of random variables, computed for a particular trial of an experiment, differs greatly
from the expected value of their average. To obtain the Law of Averages, we introduced
the notion of sets of i.i.d. random variables.

8.11.1 Terms and Theorems

8.1-8.2 Summary
TERMS
chance pips
countably infinite sample space probability
discrete sample space probability density
disjoint union probability density function
element probability of the outcome
event sample space
experiment spots
fair subset
frequency interpretation uniform probability density function
occur value
outcome

THEOREMS

Elementary Probability Facts
Probability of the Complement

8.3 Summary

TERMS

Bernoulli process Probability Multiplication Principle
Bernoulli trial process Probability of Cross Product Events
b(n; k, p) Product of Sums Principle
cross product success
cross product sample space trials
failure

THEOREMS

Probability Density on a Cross Product
Sample Space Probability of Events of Cross Product
Probability of k Successes in a Bernoulli Form
Process

8.5 Summary

TERMS

conditional probability dependent trial independent
communication channel disjoint events independent set of events
reliability independence