Probability, Statistics, and Random Processes for Engineers , 4/e (IE-Paperback)
Henry Stark , John Woods
- 出版商: Prentice Hall
- 出版日期: 2011-12-31
- 售價: $1,250
- 語言: 英文
- 頁數: 704
- ISBN: 0273752286
- ISBN-13: 9780273752288
-
相關分類:
機率統計學 Probability-and-statistics
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商品描述
<內容簡介>
1 Introduction to Probability
- 1.1 Introduction: Why Study Probability?
- 1.2 The Different Kinds of Probability
- 1.3 Misuses, Miscalculations, and Paradoxes in Probability
- 1.4 Sets, Fields, and Events
- 1.5 Axiomatic Definition of Probability
- 1.6 Joint, Conditional, and Total Probabilities; Independence
- 1.7 Bayes’ Theorem and Applications
- 1.8 Combinatorics 38
- 1.9 Bernoulli Trials–Binomial and Multinomial Probability Laws
- 1.10 Asymptotic Behavior of the Binomial Law: The Poisson Law
- 1.11 Normal Approximation to the Binomial Law
2 Random Variables
- 2.1 Introduction
- 2.2 Definition of a Random Variable
- 2.3 Cumulative Distribution Function
- 2.4 Probability Density Function (pdf)
- 2.5 Continuous, Discrete, and Mixed Random Variables
- 2.6 Conditional and Joint Distributions and Densities
- 2.7 Failure Rates
3 Functions of Random Variables
- 3.1 Introduction
- 3.2 Solving Problems of the Type Y = g(X)
- 3.3 Solving Problems of the Type Z = g(X, Y )
- 3.4 Solving Problems of the Type V = g(X, Y ), W = h(X, Y )
- 3.5 Additional Examples
4 Expectation and Moments
- 4.1 Expected Value of a Random Variable
- 4.2 Conditional Expectations
- 4.3 Moments of Random Variables
- 4.4 Chebyshev and Schwarz Inequalities
- 4.5 Moment-Generating Functions
- 4.6 Chernoff Bound
- 4.7 Characteristic Functions
- 4.8 Additional Examples
5 Random Vectors
- 5.1 Joint Distribution and Densities
- 5.2 Multiple Transformation of Random Variables
- 5.3 Ordered Random Variables
- 5.4 Expectation Vectors and Covariance Matrices
- 5.5 Properties of Covariance Matrices
- 5.6 The Multidimensional Gaussian (Normal) Law
- 5.7 Characteristic Functions of Random Vectors
6 Statistics: Part 1 Parameter Estimation
- 6.1 Introduction
- 6.2 Estimators
- 6.3 Estimation of the Mean
- 6.4 Estimation of the Variance and Covariance
- 6.5 Simultaneous Estimation of Mean and Variance
- 6.6 Estimation of Non-Gaussian Parameters from Large Samples
- 6.7 Maximum Likelihood Estimators
- 6.8 Ordering, more on Percentiles, Parametric Versus Nonparametric Statistics
- 6.9 Estimation of Vector Means and Covariance Matrices
- 6.10 Linear Estimation of Vector Parameters
7 Statistics: Part 2 Hypothesis Testing
- 7.1 Bayesian Decision Theory
- 7.2 Likelihood Ratio Test
- 7.3 Composite Hypotheses
- 7.4 Goodness of Fit
- 7.5 Ordering, Percentiles, and Rank
8 Random Sequences
- 8.1 Basic Concepts
- 8.2 Basic Principles of Discrete-Time Linear Systems
- 8.3 Random Sequences and Linear Systems
- 8.4 WSS Random Sequences
- 8.5 Markov Random Sequences
- 8.6 Vector Random Sequences and State Equations
- 8.7 Convergence of Random Sequences
- 8.8 Laws of Large Numbers
9 Random Processes
- 9.1 Basic Definitions
- 9.2 Some Important Random Processes
- 9.3 Continuous-Time Linear Systems with Random Inputs
- 9.4 Some Useful Classifications of Random Processes
- 9.5 Wide-Sense Stationary Processes and LSI Systems
- 9.6 Periodic and Cyclostationary Processes
- 9.7 Vector Processes and State Equations
Appendix A Review of Relevant Mathematics
- A.1 Basic Mathematics
- A.2 Continuous Mathematics
- A.3 Residue Method for Inverse Fourier Transformation
- A.4 Mathematical Induction
Appendix B Gamma and Delta Functions
- B.1 Gamma Function
- B.2 Incomplete Gamma Function
- B.3 Dirac Delta Function
Appendix C Functional Transformations and Jacobians
- C.1 Introduction
- C.2 Jacobians for n = 2
- C.3 Jacobian for General n
Appendix D Measure and Probability
- D.1 Introduction and Basic Ideas
- D.2 Application of Measure Theory to Probability
Appendix E Sampled Analog Waveforms and Discrete-time Signals
Appendix F Independence of Sample Mean and Variance for Normal Random Variables
Appendix G Tables of Cumulative Distribution Functions: the Normal, Student t, Chi-square, and F
Index
商品描述(中文翻譯)
內容簡介
1 概率介紹
1.1 介紹:為什麼要學習概率?
1.2 不同類型的概率
1.3 概率的誤用、計算錯誤和悖論
1.4 集合、場和事件
1.5 概率的公理定義
1.6 聯合、條件和總概率;獨立性