**Statistics for Engineers and Scientists, Sixth Edition**

William Navidi

**CONTENTS**

Preface xi

Chapter 1

Sampling and Descriptive Statistics 1

Introduction 1

1.1 Sampling 3

1.2 Summary Statistics 13

1.3 Graphical Summaries 25

Chapter 2

Probability 48

Introduction 48

2.1 Basic Ideas 48

2.2 Counting Methods 62

2.3 Conditional Probability and

Independence 69

2.4 Random Variables 90

2.5 Linear Functions of Random

Variables 116

2.6 Jointly Distributed Random

Variables 127

Chapter 3

Propagation of Error 164

Introduction 164

3.1 Measurement Error 164

3.2 Linear Combinations of

Measurements 170

3.3 Uncertainties for Functions of One

Measurement 179

3.4 Uncertainties for Functions of

Several Measurements 185

Chapter 4

Commonly Used Distributions 200

Introduction 200

4.1 The Bernoulli Distribution 200

4.2 The Binomial Distribution 203

4.3 The Poisson Distribution 215

4.4 Some Other Discrete Distributions 230

4.5 The Normal Distribution 241

4.6 The Lognormal Distribution 256

4.7 The Exponential Distribution 262

4.8 Some Other Continuous

Distributions 272

4.9 Some Principles of Point

Estimation 280

4.10 Probability Plots 285

4.11 The Central Limit Theorem 290

4.12 Simulation 303

Chapter 5

Confidence Intervals 323

Introduction 323

5.1 Confidence Intervals for a Population

Mean, Variance Known 324

5.2 Confidence Intervals for a Population

Mean, Variance Unknown 336

5.3 Confidence Intervals for

Proportions 350

5.4 Confidence Intervals for the Difference

Between Two Means 356

5.5 Confidence Intervals for the Difference

Between Two Proportions 369

5.6 Confidence Intervals with Paired

Data 374

5.7 Confidence Intervals for the Variance

and Standard Deviation of a Normal

**Population** 379

5.8 Prediction Intervals and Tolerance

Intervals 384

5.9 Using Simulation to Construct

Confidence Intervals 388

Chapter 6

Hypothesis Testing 405

Introduction 405

6.1 Tests for a Population Mean, Variance

Known 405

6.2 Drawing Conclusions from the Results

of Hypothesis Tests 416

6.3 Tests for a Population Mean, Variance

Unknown 425

6.4 Tests for a Population Proportion 433

6.5 Tests for the Difference Between Two

Means 439

6.6 Tests for the Difference Between

Two Proportions 457

6.7 Tests with Paired Data 463

6.8 Distribution-Free Tests 469

6.9 Tests with Categorical Data 478

6.10 Tests for Variances of Normal

Populations 488

6.11 Fixed-Level Testing 494

6.12 Power 500

6.13 Multiple Tests 509

6.14 Using Simulation to Perform

Hypothesis Tests 513

Chapter 7

Correlation and Simple Linear

Regression 526

Introduction 526

7.1 Correlation 526

7.2 The Least-Squares Line 544

7.3 Uncertainties in the Least-Squares

Coefficients

561

7.4 Checking Assumptions and

Transforming Data 583

Chapter 8

Multiple Regression 616

Introduction 616

8.1 The Multiple Regression Model 616

8.2 Confounding and

Collinearity 633

8.3 Model Selection 642

Chapter 9

Factorial Experiments 676

Introduction 676

9.1 One-Factor Experiments 676

9.2 Pairwise Comparisons in One-Factor

Experiments 700

9.3 Two-Factor Experiments 713

9.4 Randomized Complete Block

Designs 738

9.5 2p Factorial Experiments 748

Chapter 10

Statistical Quality Control 778

Introduction 778

10.1 Basic Ideas 778

10.2 Control Charts for Variables 781

10.3 Control Charts for Attributes 801

10.4 The CUSUM Chart 806

10.5 Process Capability 810

Appendix A: Tables 817

Appendix B: Partial

Derivatives 842

Appendix C: Data Sets 844

Appendix D: References 847

Answers to Selected Exercises 849

Index 921