Introduction to Probability 1st Edition Anderson Solutions Manual

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Introduction to Probability 1st Edition Anderson Solutions Manual.

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Introduction to Probability 1st Edition Anderson Solutions Manual

Product details:

  • ISBN-10 ‏ : ‎ 9781108415859
  • ISBN-13 ‏ : ‎ 978-1108415859
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This classroom-tested textbook is an introduction to probability theory, with the right balance between mathematical precision, probabilistic intuition, and concrete applications. Introduction to Probability covers the material precisely, while avoiding excessive technical details. After introducing the basic vocabulary of randomness, including events, probabilities, and random variables, the text offers the reader a first glimpse of the major theorems of the subject: the law of large numbers and the central limit theorem. The important probability distributions are introduced organically as they arise from applications. The discrete and continuous sides of probability are treated together to emphasize their similarities. Intended for students with a calculus background, the text teaches not only the nuts and bolts of probability theory and how to solve specific problems, but also why the methods of solution work.

Table contents:

1. Some Motivating Examples

2. Some Fundamental Concepts

3. The Concept of Probability and Basic Results

4. Conditional Probability and Independence

5. Numerical Characteristics of a Random Variable

6. Some Special Distributions

7. Joint Probability Density Function of Two Random Variables and Related Quantities

8. Joint Moment Generating Function, Covariance and Correlation Coefficient of Two Random Variables

9. Some Generalizations to k Random Variables, and Three Multivariate Distributions

10. Independence of Random Variables and Some Applications

11. Transformation of Random Variables

12. Two Modes of Convergence, the Weak Law of Large Numbers, the Central Limit Theorem, and Further Results

13. An Overview of Statistical Inference
Appendix
Tables
Some Notation and Abbreviations
Answers to the Even-numbered Exercises

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