Introduction to Probability and Statistics for Engineers and Scientists (eBook)

Sheldon M. Ross (Autor)

eBook Download: PDF

2004 | 3. Auflage
640 Seiten
Elsevier Science (Verlag)
978-0-08-047031-3 (ISBN)

Infos

Introduction to Probability and Statistics for Engineers and Scientists, Third Edition, provides an introduction to applied probability and statistics for engineering or science majors . This updated text emphasizes the manner in which probability yields insight into statistical problems, ultimately resulting in an intuitive understanding of the statistical procedures most often used by practicing engineers and scientists. The Third Edition includes new exercises, examples, homework problems, updated statistical material, and more. New exercises and data examples include: the one-sided Chebyshev inequality for data; logistics distribution and logistic regression; estimation and testing in proofreader problems; and product form estimates of life distributions. Real data sets are incorporated in a wide variety of exercises and examples throughout the book, and the enclosed CD-ROM includes unique, easy-to-use software that automates the required computations. This book is intended primarily for undergraduates in engineering and the sciences, and would be of particular interest to students in Industrial Engineering, Operations Research, Statistics, Mathematics, Computer Science, Electrical Engineering, Civil Engineering, Chemical Engineering, and Quantitative Business. It could also be of value in a graduate introductory course in probability and statistics.

New in this edition:
* New exercises and data examples including:
- The One-sided Chebyshev Inequality for Data
- The Logistics Distribution and Logistic Regression
- Estimation and Testing in proofreader problems
- Product Form Estimates of Life Distributions
- Observational Studies
* Updated statistical material
* New, contemporary applications
Hallmark features:
* Reflects Sheldon Ross's masterfully clear exposition
* Contains numerous examples, exercises, and homework problems
* Unique, easy-to-use software automates required computations
* Applies probability theory to everyday statistical problems and situations
* Careful development of probability, modeling, and statistical procedures leads to intuitive understanding
* Instructor's Solutions Manual is available to adopters

Sheldon M. Ross is a professor in the Department of Industrial Engineering and Operations Research at the University of Southern California. He received his Ph.D. in statistics at Stanford University in 1968. He has published many technical articles and textbooks in the areas of statistics and applied probability. Among his texts are A First Course in Probability, Introduction to Probability Models, Stochastic Processes, and Introductory Statistics. Professor Ross is the founding and continuing editor of the journal Probability in the Engineering and Informational Sciences. He is a Fellow of the Institute of Mathematical Statistics, and a recipient of the Humboldt US Senior Scientist Award.

Inhalt

Front Cover 1
Introduction to Probability and Statistics for Engineers and Scientists 4
Copyright Page 5
Contents 8
Preface 14
Chapter 1. Introduction to Statistics 18
1.1 Introduction 18
1.2 Data Collection and Descriptive Statistics 18
1.3 Inferential Statistics and Probability Models 19
1.4 Populations and Samples 20
1.5 A Brief History of Statistics 20
Chapter 2. Descriptive Statistics 26
2.1 Introduction 26
2.2 Describing Data Sets 26
2.3 Summarizing Data Sets 34
2.4 Chebyshev's Inequality 44
2.5 Normal Data Sets 48
2.6 Paired Data Sets and the Sample Correlation Coefficient 50
Chapter 3. Elements of Probability 72
3.1 Introduction 72
3.2 Sample Space and Events 73
3.3 Venn Diagrams and the Algebra of Events 75
3.4 Axioms of Probability 76
3.5 Sample Spaces Having Equally Likely Outcomes 78
3.6 Conditional Probability 84
3.7 Bayes' Formula 87
3.8 Independent Events 93
Chapter 4. Random Variables and Expectation 106
4.1 Random Variables 106
4.2 Types of Random Variables 109
4.3 Jointly Distributed Random Variables 112
4.4 Expectation 124
4.5 Properties of the Expected Value 128
4.6 Variance 135
4.7 Covariance and Variance of Sums of Random Variables 138
4.8 Moment Generating Functions 143
4.9 Chebyshev's Inequality and the Weak Law of Large Numbers 144
Chapter 5. Special Random Variables 158
5.1 The Bernoulli and Binomial Random Variables 158
5.2 The Poisson Random Variable 165
5.3 The Hypergeometric Random Variable 173
5.4 The Uniform Random Variable 177
5.5 Normal Random Variables 185
5.6 Exponential Random Variables 192
5.7 The Gamma Distribution 199
5.8 Distributions Arising From the Normal 202
5.9 The Logistics Distribution 209
Chapter 6. Distributions of Sampling Statistics 218
6.1 Introduction 218
6.2 The Sample Mean 219
6.3 The Central Limit Theorem 221
6.4 The Sample Variance 230
6.5 Sampling Distributions From a Normal Population 231
6.6 Sampling From a Finite Population 234
Chapter 7. Parameter Estimation 246
7.1 Introduction 246
7.2 Maximum Likelihood Estimators 247
7.3 Interval Estimates 257
7.4 Estimating the Difference in Means of Two Normal Populations 270
7.5 Approximate Confidence Interval for the Mean of a Bernoulli Random Variable 277
7.6 Confidence Interval of the Mean of the Exponential Distribution 282
7.7 Evaluating a Point Estimator 283
7.8 The Bayes Estimator 289
Chapter 8. Hypothesis Testing 308
8.1 Introduction 308
8.2 Significance Levels 309
8.3 Tests Concerning the Mean of a Normal Population 310
8.4 Testing the Equality of Means of Two Normal Populations 329
8.5 Hypothesis Tests Concerning the Variance of a Normal Population 338
8.6 Hypothesis Tests in Bernoulli Populations 340
8.7 Tests Concerning the Mean of a Poisson Distribution 347
Chapter 9. Regression 368
9.1 Introduction 368
9.2 Least Squares Estimators of the Regression Parameters 370
9.3 Distribution of the Estimators 372
9.4 Statistical Inferences About the Regression Parameters 378
9.5 The Coefficient of Determination and the Sample Correlation Coefficient 393
9.6 Analysis of Residuals: Assessing the Model 395
9.7 Transforming to Linearity 398
9.8 Weighted Least Squares 401
9.9 Polynomial Regression 408
9.10 Multiple Linear Regression 411
9.11 Logistic Regression Models for Binary Output Data 427
Chapter 10. Analysis of Variance 456
10.1 Introduction 456
10.2 An Overview 457
10.3 One-Way Analysis of Variance 459
10.4 Two-Factor Analysis of Variance: Introduction and Parameter Estimation 471
10.5 Two-Factor Analysis of Variance: Testing Hypotheses 475
10.6 Two-Way Analysis of Variance With Interaction 480
Chapter 11. Goodness of Fit Tests and Categorical Data Analysis 500
11.1 Introduction 500
11.2 Goodness of Fit Tests When All Parameters are Specified 501
11.3 Goodness of Fit Tests When Some Parameters are Unspecified 510
11.4 Tests of Independence in Contingency Tables 512
11.5 Tests of Independence in Contingency Tables Having Fixed Marginal Totals 516
11.6 The Kolmogorov–smirnov Goodness of Fit Test for Continuous Data 521
Chapter 12. Nonparametric Hypothesis Tests 532
12.1 Introduction 532
12.2 The Sign Test 532
12.3 The Signed Rank Test 536
12.4 The Two-Sample Problem 542
12.5 The Runs Test for Randomness 550
Chapter 13. Quality Control 562
13.1 Introduction 562
13.2 Control Charts for Average Values: The X -Control Chart 563
13.3 S-Control Charts 571
13.4 Control Charts for the Fraction Defective 574
13.5 Control Charts for Number of Defects 576
13.6 Other Control Charts for Detecting Changes in the Population Mean 580
Chapter 14. Life Testing 598
14.1 Introduction 598
14.2 Hazard Rate Functions 598
14.3 The Exponential Distribution in Life Testing 601
14.4 A Two-Sample Problem 615
14.5 The Weibull Distribution in Life Testing 617
Appendix of Tables 628
Index 634

Produkt-Details

• Erscheint lt. Verlag: 21.7.2004
• Sprache: englisch
• Themenwelt: Mathematik / Informatik ► Mathematik ► Angewandte Mathematik
• Themenwelt: Mathematik / Informatik ► Mathematik ► Statistik
• Themenwelt: Mathematik / Informatik ► Mathematik ► Wahrscheinlichkeit / Kombinatorik
• Themenwelt: Technik ► Bauwesen
• ISBN-10: 0-08-047031-9 / 0080470319
• ISBN-13: 978-0-08-047031-3 / 9780080470313