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