Statistical thinking: improving business performance

TABLE OF CONTENTS Introduction to JMP 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 Improvement Approaches Require Statistical Thinking Principles of Statistical Thinking Applications of Statistical Thinking Summary and Looking Forward Exercises: Chapter 1 Chapter 2 Data: The Missing Link Why Do We Need Data? Types of Data All Data are Not Created Equal Practical Sampling Tips to Ensure Data Quality What about Data Quantity? Every Data Set Has a Story: The Data Pedigree The Measurement System Summarizing Data Summary and Looking Forward Exercises: Chapter 2 Chapter 3 Statistical Thinking Strategy Case Study: The Effect of Advertising on Sales Case Study: Improvement of a Soccer Team's Performance Statistical Thinking Strategy Variation in Business Processes Synergy between Data and Subject Matter Knowledge Dynamic Nature of Business Processes Value of Graphics-Discovering the Unexpected Summary and Looking Forward Project Update Exercises: Chapter 3 Chapter 4 Understanding Business Processes Examples of Business Processes SIPOC Model for Processes Identifying Business Processes Analysis of Business Processes Systems of Processes Summary and Looking Forward Project Update Exercises: Chapter 4 Part Two Holistic Improvement: Frameworks and Basic Tools Chapter 5 Holistic Improvement: Tactics to Deploy Statistical Thinking Case Study: Resolving Customer Complaints of Baby Wipe Flushability The Problem-Solving Framework Case Study: Reducing Resin Output Variation The Process Improvement Framework Statistical Engineering Statistical Engineering Case Study: Predicting Corporate Defaults A Framework for Statistical Engineering Projects Summary and Looking Forward Project Update Exercises: Chapter 5 Chapter 6 Process Improvement and Problem-Solving Tools Practical Tools Knowledge-Based Tools Graphical Tools Analytical Tools Summary and Looking Forward Project Update Exercises: Chapter 6 Part Three Formal Statistical Methods Chapter 7 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 Observational Data Summary and Looking Forward Project Update Exercises: Chapter 7 Chapter 8 Using Process Experimentation to Build Models Randomized versus Observational Studies Why Do We Need a Statistical Approach? Examples of Process Experiments Problem-Solving and Process Improvement are Sequential Statistical Approach to Experimentation Two-Factor Experiments: A Case Study Three-Factor Experiments: A Case Study Larger Experiments Blocking, Randomization, and Center Points Summary and Looking Forward Project Update Exercises: Chapter 8 Chapter 9 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 and Looking Forward Project Update Exercises: Chapter 9 Chapter 10 Underlying Theory of Statistical Inference Applications of the Theory Theoretical Framework of Statistical Inference Probability Distributions Sampling Distributions Linear Combinations Transformations

How statistical thinking and methodology can help you make crucial business decisions. Straightforward and insightful, Statistical Thinking: Improving Business Performance, Second Edition, prepares you for business leadership by developing your capacity to apply statistical thinking to improve business processes. Unique and compelling, this book shows you how to derive actionable conclusions from data analysis, solve real problems, and improve real processes. Here, you'll discover how to implement statistical thinking and methodology in your work to improve business performance. Explores why statistical thinking is necessary and helpful. Provides case studies that illustrate how to integrate several statistical tools into the decision-making process. Facilitates and encourages an experiential learning environment to enable you to apply the material to actual problems. With an in-depth discussion of JMP software, the new edition of this important book focuses on skills to improve business processes, including collecting data appropriate for a specified purpose, recognizing limitations in existing data, and understanding the limitations of statistical analyses