TAILIEUCHUNG - Lecture Discrete mathematics and its applications - Lecture 10

In this lesson you will learn about the types of operating systems and the services they provide. Then you will learn about some of the enhancements you can make to your OS using utility software. | Discrete Probability Chapter 7 With Question/Answer Animations Copyright © McGraw-Hill Education. All rights reserved. No reproduction or distribution without the prior written consent of McGraw-Hill Education. Chapter Summary Introduction to Discrete Probability Probability Theory Bayes’ Theorem Expected Value and Variance An Introduction to Discrete Probability Section Section Summary Finite Probability Probabilities of Complements and Unions of Events Probabilistic Reasoning Probability of an Event We first study Pierre-Simon Laplace’s classical theory of probability, which he introduced in the 18th century, when he analyzed games of chance. We first define these key terms: An experiment is a procedure that yields one of a given set of possible outcomes. The sample space of the experiment is the set of possible outcomes. An event is a subset of the sample space. Here is how Laplace defined the probability of an event: Definition: If S is a finite sample space of equally likely outcomes, and E is an event, that is, a subset of S, then the probability of E is p(E) =

• Kỹ thuật lập trình
• Discrete mathematics
• Discrete mathematics applications
• Discrete Structures
• Mathematical Reasoning
• Combinatorial Analysis
• Computer Science
• Discrete Probability
• Lecture Discrete Mathematics I
• Discrete Mathematics I
• Bài giảng Toán rời rạc
• Probability rules
• andom variables
• Probability models
• Applications discrete mathematics
• The foundations
• Basic structures
• The integers
• Number theory