Table of contents provided by Syndetics

• Case Histories (p. xiii)
• Preface to the Third Edition (p. xv)
• Preface to the Second Edition (p. xix)
• Preface to the First Edition (p. xxiii)
• Part 1 Basics of Interpretation of Data
• Chapter 1. Variables Data: An Introduction (p. 3)
• 1.1 Introduction--An Experience with Data (p. 3)
• 1.2 Variability (p. 5)
• 1.3 Organizing Data (p. 7)
• 1.4 Grouping Data When n is Large (p. 8)
• 1.5 The Arithmetic Average or Mean--Central Value (p. 11)
• 1.6 Measures of Variation (p. 12)
• 1.7 Normal Probability Plots (p. 18)
• 1.8 Prediction Regarding Sampling Variation: The Normal Curve (p. 20)
• 1.9 Series of Small Samples from a Production Process (p. 27)
• 1.10 Changes in Sample Size: Predictions about X and [sigma] (p. 28)
• 1.11 How Large a Sample Is Needed to Estimate a Process Average? (p. 30)
• 1.12 Sampling and a Second Method of Computing [sigma] (p. 31)
• 1.13 Some Important Remarks about the Two Estimates (p. 34)
• 1.14 Stem-and-Leaf (p. 36)
• 1.15 Box-Plots (p. 37)
• 1.16 Tolerance Intervals for Populations (p. 39)
• 1.17 A Note on Notation (p. 41)
• 1.18 Summary (p. 43)
• 1.19 Practice Exercises (p. 43)
• Chapter 2. Ideas from Time Sequences of Observations (p. 53)
• 2.1 Introduction (p. 53)
• 2.2 Data from a Scientific or Production Process (p. 56)
• 2.3 Signals and Risks (p. 57)
• 2.4 Run Criteria (p. 59)
• 2.5 Shewhart Control Charts for Variables (p. 65)
• 2.6 Probabilities Associated with an X-Control Chart: Operating-Characteristic Curves (p. 74)
• 2.7 Control Charts for Trends (p. 91)
• 2.8 Practice Exercises (p. 99)
• Chapter 3. Ideas from Outliers--Variables Data (p. 105)
• 3.1 Introduction (p. 105)
• 3.2 Other Objective Tests for Outliers (p. 109)
• 3.3 Two Suspected Outliers on the Same End of a Sample of n (Optional) (p. 111)
• 3.4 Practice Exercises (p. 113)
• Chapter 4. Variability--Estimating and Comparing (p. 115)
• 4.1 Introduction (p. 115)
• 4.2 Statistical Efficiency and Bias in Variability Estimates (p. 115)
• 4.3 Estimating [sigma] and [sigma superscript 2] from Data: One Sample of Size n (p. 117)
• 4.4 Data from n Observations Consisting of k Subsets of n[subscript g] = r: Two Procedures (p. 118)
• 4.5 Comparing Variabilities of Two Populations (p. 120)
• 4.6 Summary (p. 129)
• 4.7 Practice Exercises (p. 131)
• Chapter 5. Attributes or Go No-Go Data (p. 133)
• 5.1 Introduction (p. 133)
• 5.2 Three Important Problems (p. 133)
• 5.3 On How to Sample (p. 143)
• 5.4 Attributes Data Which Approximate a Poisson Distribution (p. 145)
• 5.5 Practice Exercises (p. 153)
• Part 2 Statistical Process Control
• Chapter 6. On Sampling to Provide a Feedback of Information (p. 157)
• 6.1 Introduction (p. 157)
• 6.2 Scientific Sampling Plans (p. 159)
• 6.3 A Simple Probability (p. 160)
• 6.4 Operating-Characteristic Curves of a Single Sampling Plan (p. 160)
• 6.5 But Is it a Good Plan? (p. 161)
• 6.6 Average Outgoing Quality (AOQ) and Its Maximum Limit (AOQL) (p. 163)
• 6.7 Computing the Average Outgoing Quality (AOQ) of Lots from a Process Producing P Percent Defective (p. 164)
• 6.8 Other Important Concepts Associated with Sampling Plans (p. 167)
• 6.9 Risks (p. 167)
• 6.10 Tabulated Sampling Plans (p. 168)
• 6.11 Feedback of Information (p. 169)
• 6.12 Where Should Feedback Begin? (p. 172)
• 6.13 Outgoing Product Quality Rating (OPQR) (p. 173)
• 6.14 Practice Exercises (p. 190)
• Chapter 7. Narrow-Limit Gauging in Process Control (p. 191)
• 7.1 Introduction (p. 191)
• 7.2 Outline of an NL-Gauging Plan (p. 192)
• 7.3 Selection of a Simple NL-Gauging Sampling Plan (p. 193)
• 7.4 Sequential NL-Gauging Plans (p. 198)
• 7.5 OC Curves of NL-Gauge Plans (p. 201)
• 7.6 Hazards (p. 204)
• 7.7 Selection of an NL-Gauge Plan (p. 208)
• 7.8 Practice Exercises (p. 209)
• Chapter 8. On Implementing Statistical Process Control (p. 211)
• 8.1 Introduction (p. 211)
• 8.2 Key Aspects of Process Quality Control (p. 212)
• 8.3 Process Control (p. 213)
• 8.4 Uses of Control Charts (p. 215)
• 8.5 Rational Subgroups (p. 216)
• 8.6 Special Control Charts (p. 216)
• 8.7 Median Chart (p. 216)
• 8.8 Standard Deviation Chart (p. 220)
• 8.9 Acceptance Control Chart (p. 221)
• 8.10 Modified Control Limits (p. 224)
• 8.11 Arithmetic and Exponentially Weighted Moving Average Charts (p. 226)
• 8.12 Cumulative Sum Charts (p. 229)
• 8.13 Precontrol (p. 243)
• 8.14 Narrow Limit Control Charts (p. 246)
• 8.15 How to Apply Control Charts (p. 246)
• 8.16 Other Control Charts (p. 250)
• 8.17 Process Capability (p. 262)
• 8.18 Process-Optimization Studies (p. 262)
• 8.19 Capability and Specifications (p. 264)
• 8.20 Process Performance (p. 268)
• 8.21 Process Improvement (p. 271)
• 8.22 Process Change (p. 271)
• 8.23 Problem Identification (p. 272)
• 8.24 Prioritization (p. 273)
• 8.25 Summary (p. 275)
• 8.26 Practice Exercises (p. 276)
• Part 3 Troubleshooting and Process Improvement (p. 280)
• Chapter 9. Some Basic Ideas and Methods of Troubleshooting (p. 281)
• 9.1 Introduction (p. 281)
• 9.2 Some Types of Independent and Dependent Variables (p. 282)
• 9.3 Some Strategies in Problem Finding, Problem Solving, and Troubleshooting (p. 284)
• 9.4 Bicking's Checklist (p. 289)
• 9.5 Practice Exercises (p. 289)
• Chapter 10. Some Concepts of Statistical Design of Experiments (p. 293)
• 10.1 Introduction (p. 293)
• 10.2 Effects (p. 294)
• 10.3 Sums of Squares (p. 297)
• 10.4 Yates Method (p. 299)
• 10.5 Blocking (p. 304)
• 10.6 Fractional Factorials (p. 304)
• 10.7 Graphical Analysis of 2[superscript p] Designs (p. 307)
• 10.8 Conclusion (p. 312)
• 10.9 Practice Exercises (p. 315)
• Chapter 11. Troubleshooting with Attributes Data (p. 319)
• 11.1 Introduction (p. 319)
• 11.2 Ideas from Sequences of Observations over Time (p. 320)
• 11.3 Decision Lines Applicable to k Points Simultaneously (p. 321)
• 11.4 Analysis of Means for Proportions (p. 329)
• 11.5 Example--Proportions (p. 330)
• 11.6 Analysis of Means for Count Data (p. 330)
• 11.7 Example--Count Data (p. 331)
• 11.8 Introduction to Case Histories (p. 332)
• 11.9 One Independent Variable with k Levels (p. 333)
• 11.10 Two Independent Variables (p. 342)
• 11.11 Three Independent Factors (p. 354)
• 11.12 A Very Important Experimental Design: 1/2 [times] 2[superscript 3] (p. 367)
• 11.13 Case History Problems (p. 371)
• 11.14 Practice Exercises (p. 376)
• Chapter 12 Special Strategies in Troubleshooting (p. 379)
• 12.1 Ideas from Patterns of Data (p. 379)
• 12.2 Disassembly and Reassembly (p. 383)
• 12.3 A Special Screening Program for Many Treatments (p. 387)
• 12.4 Other Screening Strategies (p. 393)
• 12.5 Relationship of One Variable to Another (p. 393)
• 12.6 Use of Transformations and ANOM (p. 397)
• 12.7 Practice Exercises (p. 405)
• Chapter 13. Comparing Two Process Averages (p. 407)
• 13.1 Introduction (p. 407)
• 13.2 Tukey's Two-Sample Test to Duckworth's Specifications (p. 407)
• 13.3 Analysis of Means, k = 2, n[subscript g] = r[subscript 1] = r[subscript 2] = r (p. 409)
• 13.4 Student's t and F Test Comparison of Two Stable Processes (p. 411)
• 13.5 Magnitude of the Difference between Two Means (p. 413)
• 13.6 Practice Exercises (p. 422)
• Chapter 14. Troubleshooting with Variables Data (p. 425)
• 14.1 Introduction (p. 425)
• 14.2 Suggestions in Planning Investigations--Primarily Reminders (p. 426)
• 14.3 A Statistical Tool for Process Change (p. 427)
• 14.4 Analysis of Means for Measurement Data (p. 428)
• 14.5 Example--Measurement Data (p. 430)
• 14.6 Analysis of Means: A 2[superscript 2] Factorial Design (p. 431)
• 14.7 Three Independent Variables: A 2[superscript 3] Factorial Design (p. 438)
• 14.8 Computational Details for Two-Factor Interactions in a 2[superscript 3] Factorial Design (p. 444)
• 14.9 A Very Important Experimental Design: 1/2 [times] 2[superscript 3] (p. 445)
• 14.10 General ANOM Analysis of 2[superscript p] and 2[superscript p-1] Designs (p. 451)
• 14.11 Practice Exercises (p. 453)
• Chapter 15. More Than Two Levels of an Independent Variable (p. 457)
• 15.1 Introduction (p. 457)
• 15.1 An Analysis of k Independent Samples--Standard Given--One Independent Variable (p. 458)
• 15.3 An Analysis of k Independent Samples--No Standard Given--One Independent Variable (p. 459)
• 15.4 Analysis of Means--No Standard Given--More Than One Independent Variable (p. 464)
• 15.5 Analysis of Two-Factor Crossed Designs (p. 465)
• 15.6 The Relation of Analysis of Means to Analysis of Variance (Optional) (p. 472)
• 15.7 Analysis of Fully Nested Designs (Optional) (p. 474)
• 15.8 Analysis of Means for Crossed Experiments--Multiple Factors (p. 479)
• 15.9 Nested Factorial Experiments (Optional) (p. 493)
• 15.10 Multifactor Experiments with Attributes Data (p. 493)
• 15.11 Analysis of Means When the Sample Sizes Are Unequal (p. 499)
• 15.12 Comparing Variabilities (p. 500)
• 15.13 Nonrandom Uniformity (p. 505)
• 15.14 Development of Analysis of Means (p. 508)
• 15.15 Practice Exercises (p. 517)
• Chapter 16. What's on the CD (p. 519)
• Chapter 17. Epilogue (p. 531)
• Appendix Tables (p. 539)
• Index (p. 575)