Rent 9780534242640 | Probability and Statistics for Engineering and the Sciences

Summary Table of Contents

This best-selling text is intended for applied introductory probability and statistics courses taken by students in engineering and the physical sciences (calculus prerequisite). It emphasizes models, methodology, and applications, rather than rigorous mathematical development and theory. It features real data in exercises and examples. Also includes:
-- A chapter on joint probability distributions that introduces the concept of a statistic and its sampling distribution
-- Many real-data sets throughout
-- Strong coverage of computer-based methods, especially in analysis of variance and regression
-- Increased coverage of data analysis in Chapter One
-- Simulation experiments and bootstrapping techniques (Ch. 5)
-- Updated material on quality control

CHAPTER 1 Introduction and Descriptive Statistics

(42)

1.1 An Overview of Probability and Statistics

(7)

1.2 Pictor... MORE

(12)

1.3 Measures of Location

(8)

1.4 Measures of Variability

(12)

Supplementary Exercises

(2)

Bibliography

(1)

CHAPTER 2 Probability

(46)

Introduction

(1)

2.1 Sample Spaces and Events

(6)

2.2 Axioms, Interpretations, and Properties of Probability

(10)

2.3 Counting Techniques

(8)

2.4 Conditional Probability

(11)

2.5 Independence

(6)

Supplementary Exercises

(4)

Bibliography

(1)

CHAPTER 3 Discrete Random Variables and Probability Distributions

(49)

Introduction

(1)

3.1 Random Variables

(5)

3.2 Probability Distributions for Discrete Random Variables

(10)

3.3 Expected Values of Discrete Random Variables

104

(9)

3.4 The Binomial Probability Distribution

113

(9)

3.5 Hypergeometric and Negative Binomial Distributions

122

(6)

3.6 The Poisson Probability Distribution

128

(5)

Supplementary Exercises

133

(4)

Bibliography

137

(1)

CHAPTER 4 Continuous Random Variables and Probability Distributions

138

(59)

Introduction

138

(1)

4.1 Continuous Random Variables and Probability Density Functions

138

(7)

4.2 Cumulative Distribution Functions and Expected Values

145

(9)

4.3 The Normal Distribution

154

(13)

4.4 The Gamma Distribution and Its Relatives

167

(7)

4.5 Other Continuous Distributions

174

(7)

4.6 Probability Plots

181

(11)

Supplementary Exercises

192

(4)

Bibliography

196

(1)

CHAPTER 5 Joint Probability Distributions and Random Samples

197

(50)

Introduction

197

(1)

5.1 Jointly Distributed Random Variables

197

(14)

5.2 Expected Values, Covariance, and Correlation

211

(7)

5.3 Statistics and Their Distributions

218

(12)

5.4 The Distribution of the Sample Mean

230

(7)

5.5 The Distribution of a Linear Combination

237

(6)

Supplementary Exercises

243

(3)

Bibliography

246

(1)

CHAPTER 6 Point Estimation

247

(28)

Introduction

247

(1)

6.1 Some General Concepts of Point Estimation

247

(16)

6.2 Methods of Point Estimation

263

(10)

Supplementary Exercises

273

(1)

Bibliography

274

(1)

CHAPTER 7 Statistical Intervals Based on a Single Sample

275

(29)

Introduction

275

(1)

7.1 Basic Properties of Confidence Intervals

276

(9)

7.2 Large-Sample Confidence Intervals for a Population Mean and Proportion

285

(6)

7.3 Intervals Based on a Normal Population Distribution

291

(7)

7.4 Confidence Intervals for the Variance and Standard Deviation of a Normal Population

298

(3)

Supplementary Exercises

301

(2)

Bibliography

303

(1)

CHAPTER 8 Tests of Hypotheses Based on a Single Sample

304

(42)

Introduction

304

(1)

8.1 Hypotheses and Test Procedures

304

(11)

8.2 Tests About a Population Mean

315

(12)

8.3 Tests Concerning a Population Proportion

327

(6)

8.4 P-Values

333

(6)

8.5 Some Comments on Selecting a Test Procedure

339

(3)

Supplementary Exercises

342

(3)

Bibliography

345

(1)

CHAPTER 9 Inferences Based on Two Samples

346

(44)

Introduction

346

(1)

9.1 z Tests and Confidence Intervals for a Difference Between Two Population Means

346

(11)

9.2 The Two-Sample t Test and Confidence Interval

357

(9)

9.3 Analysis of Paired Data

366

(9)

9.4 Inferences Concerning a Difference Between Population Proportions

375

(7)

9.5 Inferences Concerning Two Population Variances

382

(4)

Supplementary Exercises

386

(3)

Bibliography

389

(1)

CHAPTER 10 The Analysis of Variance

390

(30)

Introduction

390

(1)

10.1 Single-Factor ANOVA

391

(10)

10.2 Multiple Comparisons in ANOVA

401

(6)

10.3 More on Single-Factor ANOVA

407

(10)

Supplementary Exercises

417

(1)

Bibliography

418

(2)

CHAPTER 11 Multifactor Analysis of Variance

420

(54)

Introduction

420

(1)

11.1 Two-Factor ANOVA with K(ij) = 1

421

(14)

11.2 Two-Factor ANOVA with K(ij) Greater than 1

435

(9)

11.3 Three-Factor ANOVA

444

11.4 2^(P) Factorial Experiments

435

Supplementary Exercises

471

(2)

Bibliography

473

(1)

CHAPTER 12 Simple Linear Regression and Correlation

474

(49)

Introduction

474

(1)

12.1 The Simple Linear Regression Model

475

(5)

12.2 Estimating Model Parameters

480

(15)

12.3 Inferences About the Slope Parameter Beta(1)

495

(7)

12.4 Inferences Concerning (XXX)(y.x) and the Prediction of Future Y Values

502

(7)

12.5 Correlation

509

(10)

Supplementary Exercises

519

(3)

Bibliography

522

(1)

CHAPTER 13 Nonlinear and Multiple Regression

523

(63)

Introduction

523

(1)

13.1 Aptness of the Model and Model Checking

523

(8)

13.2 Regression with Transformed Values

531

(8)

13.3 Polynomial Regression

539

(11)

13.4 Multiple Regression Analysis

550

(18)

13.5 Other Issues in Multiple Regression

568

(13)

Supplementary Exercises

581

(3)

Bibliography

584

(2)

CHAPTER 14 The Analysis of Categorical Data

586

(36)

Introduction

586

(1)

14.1 Goodness-of-Fit Tests When Category Probabilities Are Completely Specified

587

(8)

14.2 Goodness of Fit for Composite Hypotheses

595

(12)

14.3 Two-Way Contingency Tables

607

(13)

Supplementary Exercises

620

(1)

Bibliography

621

(1)

CHAPTER 15 Distribution-Free Procedures

622

(36)

Introduction

622

(1)

15.1 The Sign Test

623

(5)

15.2 The Wilcoxon Signed-Rank Test

628

(10)

15.3 The Wilcoxon Rank-Sum Test

638

(6)

15.4 Distribution-Free Confidence Intervals

644

(7)

15.5 Distribution-Free ANOVA

651

(5)

Supplementary Exercises

656

(1)

Bibliography

657

(1)

CHAPTER 16 Quality Control Methods

658

(41)

Introduction

658

(1)

16.1 General Comments on Control Charts

659

(2)

16.2 Control Charts for Process Location

661

(10)

16.3 Control Charts for Process Variation

671

(4)

16.4 Control Charts for Attributes

675

(6)

16.5 CUSUM Procedures

681

(9)

16.6 Acceptance Sampling

690

(7)

Supplementary Exercises

697

(1)

Bibliography

698

(1)

Appendix Tables

699

(20)

A.1 Cumulative Binomial Probabilities

700

(2)

A.2 Cumulative Poisson Probabilities

702

(2)

A.3 Standard Normal Curve Areas

704

(2)

A.4 The Incomplete Gamma Function

706

(1)

A.5 Critical Values t(Alpha, v) for the t Distribution

707

(1)

A.6 Critical Values X(Alpha^(2), v) for the Chi-Squared Distribution

708

(1)

A.7 Critical Values F(Alpha, v(1), v(2)) for the F Distribution

709

(2)

A.8 Critical Values Q(Alpha, m, v) for the Studentized Range Distribution

711

(2)

A.9 Upper-Tail Critical Values and Probabilities for the Null Distribution of the Wilcoxon Signed-Rank Statistic S(+)

713

(1)

A.10 Upper-Tail Critical Values and Probabilities for the Null Distribution of the Wilcoxon Rank-Sum Statistic W

714

(1)

A.11 Critical Constant c for the Wilcoxon Signed-Rank Interval

715

(1)

A.12 Critical Constant c for the Wilcoxon Rank-Sum Interval

716

(1)

A.13 Curves of Beta = P (Type II Error) for t Tests

717

(1)

A.14 Critical Values c(Alpha) for the Test of Normality Based on r from a Normal Probability Plot

718

(1)

Answers

719

(16)

Index

735

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