Statistical Thinking Improving Business Performance

ISBN-10: 1118094778
ISBN-13: 9781118094778
Edition: 2nd 2012
Authors: Roger Hoerl, Ron Snee
List price: $90.00 Buy it from $72.50
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Description: Succeed with statistical thinkingRoger Hoerl and Ronald D. Snee's Statistical Thinking: Improving Business Performance prepares you for business leadership by developing your capacity to apply statistical thinking to improve business processes.  More...

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Book details

List price: $90.00
Edition: 2nd
Copyright year: 2012
Publisher: John Wiley & Sons, Limited
Publication date: 4/27/2012
Binding: Hardcover
Pages: 544
Size: 7.50" wide x 10.25" long x 1.75" tall
Weight: 2.618
Language: English

Succeed with statistical thinkingRoger Hoerl and Ronald D. Snee's Statistical Thinking: Improving Business Performance prepares you for business leadership by developing your capacity to apply statistical thinking to improve business processes. Unique and compelling, this book shows the reader how to derive actionable conclusions from data analysis, solve real problems, and improve real processes. The authors clearly illustrate how to implement statistical thinking and methodology in your work to improve business performance.HighlightsThis book begins with a discussion of why statistical thinking is necessary and helpful, and then provides case studies that illustrate how to integrate several statistical tools into the decision-making process.The authors facilitate and encourage an experiential learning environment so that the reader may develop competency by applying the material to actual problems.Students have the opportunity to work in teams on case studies in each chapter in addition to the course project.Because easy-to-use data analysis software is so widely used and available, the book emphasizes conceptual understanding over formulas and calculations.Formal statistical methods are, in most cases, illustrated with Microsoft® Excel, MINITAB, and JMP®.

Preface
Introduction to JMP
statistical Thinking Concepts
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
Notes
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
Notes
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
Notes
Statistical Engineering: Frameworks and Basic Tools
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
Notes
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
Notes
Formal Statistical Methods
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
Notes
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
Notes
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
Notes
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
Notes
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
Notes
Effective Teamwork
Presentations and Report Writing
More on Surveys
More on Regression
More on Design of Experiments
More on inference Tools
More on Probability Distributions
Process Design (Reengineering)
t Critical Values
Standard Normal Probabilities (Cumulative z Curve Areas)
Index

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