Solution Manual for Probability, Statistics, and Random Processes for Engineers, 4/E 4th Edition Henry Stark, John Woods

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Product details:

• ISBN-10 ‏ : ‎ 0132311232
• ISBN-13 ‏ : ‎ 978-0132311236
• Author: Henry Stark; John Woods

For courses in Probability and Random Processes. Probability, Statistics, and Random Processes for Engineers, 4e is a useful text for electrical and computer engineers. This book is a comprehensive treatment of probability and random processes that, more than any other available source, combines rigor with accessibility. Beginning with the fundamentals of probability theory and requiring only college-level calculus, the book develops all the tools needed to understand more advanced topics such as random sequences, continuous-time random processes, and statistical signal processing. The book progresses at a leisurely pace, never assuming more knowledge than contained in the material already covered. Rigor is established by developing all results from the basic axioms and carefully defining and discussing such advanced notions as stochastic convergence, stochastic integrals and resolution of stochastic processes.

Table of contents:

1 Introduction to Probability 1

1.1 Introduction: Why Study Probability? 1

1.2 The Different Kinds of Probability 2

Probability as Intuition 2

Probability as the Ratio of Favorable to Total Outcomes (Classical Theory) 3

Probability as a Measure of Frequency of Occurrence 4

Probability Based on an Axiomatic Theory 5

1.3 Misuses, Miscalculations, and Paradoxes in Probability 7

1.4 Sets, Fields, and Events 8

Examples of Sample Spaces 8

1.5 Axiomatic Definition of Probability 15

1.6 Joint, Conditional, and Total Probabilities; Independence 20

Compound Experiments 23

1.7 Bayes’ Theorem and Applications 35

1.8 Combinatorics 38

Occupancy Problems 42

Extensions and Applications 46

1.9 Bernoulli Trials–Binomial and Multinomial Probability Laws 48

Multinomial Probability Law 54

1.10 Asymptotic Behavior of the Binomial Law: The Poisson Law 57

1.11 Normal Approximation to the Binomial Law 63

Summary 65

Problems 66

References 77

2 Random Variables 79

2.1 Introduction 79

2.2 Definition of a Random Variable 80

2.3 Cumulative Distribution Function 83

Properties ofFX(x) 84

Computation ofFX(x) 85

2.4 Probability Density Function (pdf) 88

Four Other Common Density Functions 95

More Advanced Density Functions 97

2.5 Continuous, Discrete, and Mixed Random Variables 100

Some Common Discrete Random Variables 102

2.6 Conditional and Joint Distributions and Densities 107

Properties of Joint CDF

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