Statistical Thinking - Improving Business Performance

Apply statistics in business to achieve performance improvement
 
Statistical Thinking: Improving Business Performance, 3rd Edition helps managers understand the role of statistics in implementing business improvements. It guides professionals who are learning statistics in order to improve performance in business and industry. It also helps graduate and undergraduate students understand the strategic value of data and statistics in arriving at real business solutions. Instruction in the book is based on principles of effective learning, established by educational and behavioral research.
 
The authors cover both practical examples and underlying theory, both the big picture and necessary details. Readers gain a conceptual understanding and the ability to perform actionable analyses. They are introduced to data skills to improve business processes, including collecting the appropriate data, identifying existing data limitations, and analyzing data graphically. The authors also provide an in-depth look at JMP software, including its purpose, capabilities, and techniques for use.
 
Updates to this edition include:
* A new chapter on data, assessing data pedigree (quality), and acquisition tools
* Discussion of the relationship between statistical thinking and data science
* Explanation of the proper role and interpretation of p-values (understanding of the dangers of "p-hacking")
* Differentiation between practical and statistical significance
* Introduction of the emerging discipline of statistical engineering
* Explanation of the proper role of subject matter theory in order to identify causal relationships
* A holistic framework for variation that includes outliers, in addition to systematic and random variation
* Revised chapters based on significant teaching experience
* Content enhancements based on student input
 
This book helps readers understand the role of statistics in business before they embark on learning statistical techniques.

List of contents

Preface xiii
 
Introduction to JMP xvii
 
Part One Statistical Thinking Concepts 1
 
Chapter 1 Need for Business Improvement 3
 
Today's Business Realities and the Need to Improve 4
 
We Now Have Two Jobs: A Model for Business Improvement 8
 
New Improvement Approaches Require Statistical Thinking 12
 
Principles of Statistical Thinking 17
 
Applications of Statistical Thinking 22
 
Summary and Looking Forward 23
 
Exercises: Chapter 1 24
 
Notes 25
 
Chapter 2 Data: The Missing Link 27
 
Why Do We Need Data? 28
 
Types of Data 29
 
All Data are Not Created Equal 32
 
Practical Sampling Tips to Ensure Data Quality 34
 
What about Data Quantity? 38
 
Every Data Set Has a Story: The Data Pedigree 40
 
The Measurement System 42
 
Summarizing Data 48
 
Summary and Looking Forward 52
 
Exercises: Chapter 2 52
 
Notes 54
 
Chapter 3 Statistical Thinking Strategy 55
 
Case Study: The Effect of Advertising on Sales 56
 
Case Study: Improvement of a Soccer Team's Performance 62
 
Statistical Thinking Strategy 71
 
Variation in Business Processes 76
 
Synergy between Data and Subject Matter Knowledge 82
 
Dynamic Nature of Business Processes 84
 
Value of Graphics--Discovering the Unexpected 86
 
Summary and Looking Forward 89
 
Project Update 89
 
Exercises: Chapter 3 90
 
Notes 91
 
Chapter 4 Understanding Business Processes 93
 
Examples of Business Processes 94
 
SIPOC Model for Processes 100
 
Identifying Business Processes 102
 
Analysis of Business Processes 103
 
Systems of Processes 119
 
Summary and Looking Forward 122
 
Project Update 123
 
Exercises: Chapter 4 124
 
Notes 126
 
Part Two Holistic Improvement: Frameworks and Basic Tools 127
 
Chapter 5 Holistic Improvement: Tactics to Deploy Statistical Thinking 129
 
Case Study: Resolving Customer Complaints of Baby Wipe Flushability 130
 
The Problem-Solving Framework 137
 
Case Study: Reducing Resin Output Variation 141
 
The Process Improvement Framework 147
 
Statistical Engineering 153
 
Statistical Engineering Case Study: Predicting Corporate Defaults 154
 
A Framework for Statistical Engineering Projects 158
 
Summary and Looking Forward 164
 
Project Update 165
 
Exercises: Chapter 5 166
 
Notes 167
 
Chapter 6 Process Improvement and Problem-Solving Tools 169
 
Practical Tools 172
 
Knowledge-Based Tools 191
 
Graphical Tools 207
 
Analytical Tools 228
 
Summary and Looking Forward 265
 
Project Update 265
 
Exercises: Chapter 6 266
 
Notes 271
 
Part Three Formal Statistical Methods 273
 
Chapter 7 Building and Using Models 275
 
Examples of Business Models 276
 
Types and Uses of Models 279
 
Regression Modeling Process 282
 
Building Models with One Predictor Variable 290
 
Building Models with Several Predictor Variables 307
 
Multicollinearity: Another Model Check 315
 
Some Limitations of Using Observational Data 317
 
Summary and Looking Forward 319
 
Project Update 321
 
Exercises: Chapter 7 321
 
Notes 346
 
Chapter 8 Using Process Experimentation to Build Models 347
 
Randomized versus Observational Studies 348
 
Why Do We Need a Statistical Approach? 350
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About the author

DR. ROGER W. HOERL is an associate professor at Union College where he teaches statistics, engineering statistics, design of experiments, regression analysis, and big data analytics. Previously, he led the Applied Statistics Laboratory at GE Global Research.
DR. RONALD D. SNEE is founder and president of Snee Associates, an authority on designing and implementing organizational improvement and cost-reduction solutions. Prior to this role, he worked at the DuPont Company in a variety of assignments. Snee has co-authored five books and published more than 330 articles on process improvement, quality, and statistics.

Summary

Apply statistics in business to achieve performance improvement

Statistical Thinking: Improving Business Performance, 3rd Edition helps managers understand the role of statistics in implementing business improvements. It guides professionals who are learning statistics in order to improve performance in business and industry. It also helps graduate and undergraduate students understand the strategic value of data and statistics in arriving at real business solutions. Instruction in the book is based on principles of effective learning, established by educational and behavioral research.

The authors cover both practical examples and underlying theory, both the big picture and necessary details. Readers gain a conceptual understanding and the ability to perform actionable analyses. They are introduced to data skills to improve business processes, including collecting the appropriate data, identifying existing data limitations, and analyzing data graphically. The authors also provide an in-depth look at JMP software, including its purpose, capabilities, and techniques for use.

Updates to this edition include:
* A new chapter on data, assessing data pedigree (quality), and acquisition tools
* Discussion of the relationship between statistical thinking and data science
* Explanation of the proper role and interpretation of p-values (understanding of the dangers of "p-hacking")
* Differentiation between practical and statistical significance
* Introduction of the emerging discipline of statistical engineering
* Explanation of the proper role of subject matter theory in order to identify causal relationships
* A holistic framework for variation that includes outliers, in addition to systematic and random variation
* Revised chapters based on significant teaching experience
* Content enhancements based on student input

This book helps readers understand the role of statistics in business before they embark on learning statistical techniques.

Product details

• Authors: Hoerl, Roger Hoerl, Roger W Hoerl, Roger W. Hoerl, Roger W. (Union College Hoerl, Roger W. Snee Hoerl, Hoerl Roger W., Ron D. Snee, Ronald D Snee, Ronald D. Snee, Snee Ronald D.
• Publisher: Wiley, John and Sons Ltd
• Languages: English
• Product format: Hardback
• Released: 31.07.2020
• EAN: 9781119605713
• ISBN: 978-1-119-60571-3
• No. of pages: 640
• Series: SAS Institute Inc; Wiley and SAS Business Series; Wiley and SAS Business
• Subjects: Social sciences, law, business > Business > Management; Wirtschaftsmathematik, Business & management, Wirtschaft u. Management, Wirtschaftsmathematik u. -statistik, Business Statistics & Math