Preface
Part One Statistical Thinking Concepts
Chapter 1 Need for Business Improvement
Today's Business Realities and the Need to Improve
We Now Have Two Jobs: A Model for Business Improvement
New Management Approaches Require Statistical Thinking
Principles of Statistical Thinking
Applications of Statistical Thinking
Summary
Chapter 2 Statistical Thinking Strategy
CASE STUDY: The Effect of Advertising on Sales
CASE STUDY: Improvement of a Soccer Team's Performance
Statistical Thinking Strategy
Context of Statistical Thinking: Statistics Discipline as a System
Variation in Business Processes
Synergy Between Data and Subject Matter Knowledge
Dynamic Nature of Business Processes
Summary
Project Update
Chapter 3 Understanding Business Processes
Examples of Business Processes
SIPOC Model for Processes
Identifying Business Processes
Analysis of Business Processes
Systems of Processes
Measurement Process
Summary
Project Update
Part Two Statistical Engineering: Frameworks and Basic Tools
Chapter 4 Statistical Engineering: Tactics to Deploy Statistical Thinking
Statistical Engineering
CASE STUDY: Reducing Resin Output Variation
CASE STUDY: Reducing Telephone Waiting Time at a Bank
Basic Process Improvement Framework
CASE STUDY: Resolving Customer Complaints of Baby Wipe Flushability
CASE STUDY: The Realized Revenue Fiasco
Basic Problem-Solving Framework
DMAIC Framework
DMAIC Case Study: Newspaper Accuracy
Summary
Project Update
Chapter 5 Process Improvement and Problem-Solving Tools
Stratification
Data Collection Tools
Basic Graphical Analysis Tools
Knowledge-Based Tools
Process Stability and Capability Tools
Summary
Project Update
Part Three Formal Statistical Methods
Chapter 6 Building and Using Models
Examples of Business Models
Types and Uses of Models
Regression Modeling Process
Building Models with One Predictor Variable
Building Models with Several Predictor Variables
Multicollinearity, another Model Check
Some Limitations of Using Existing Data
Summary
Project Update
Chapter 7 Using Process Experimentation to Build Models
Why Do We Need a Statistical Approach?
Examples of Process Experiments
Statistical Approach to Experimentation
Two-Factor Experiments: A Case Study
Three-Factor Experiments: A Case Study
Larger Experiments
Blocking, Randomization, and Center Points
Summary
Project Update
Chapter 8 Applications of Statistical Inference Tools
Examples of Statistical Inference Tools
Process of Applying Statistical Inference
Statistical Confidence and Prediction Intervals
Statistical Hypothesis Tests
Tests for Continuous Data
Test for Discrete Data: Comparing Two or More Proportions
Test for Regression Analysis: Test on a Regression Coefficient
Sample Size Formulas
Summary
Project Update
Chapter 9 Underlying Theory of Statistical Inference
Applications of the Theory
Theoretical Framework of Statistical Inference
Types of Data
Probability Distributions
Sampling Distributions
Linear Combinations
Transformations
Summary
Project Update
Chapter 10 Summary and Path Forward
A Personal Case Study by Tom Pohlen
Review of the Statistical Thinking Approach
Text Summary
Potential Next Steps to Deeper Understanding of Statistical Thinking
Project Summary and Debriefing
Appendices
Appendix A Effective Teamwork
Appendix B Presentations and Report Writing
Appendix C More on Surveys
Appendix D More on Regression
Appendix E More on Design of Experiments
Appendix F More on Inference Tools
Appendix G More on Probability Distribution
Appendix H Process Design (Reengineering)
Appendix I t Critical Values
Appendix J Standard Normal Probabilities (Cumulative z Curve Areas)
Index
