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Statistics Articles, Reports, Handbooks and Guides

• Statistical Process Control, The Alpha and Omega of Six Sigma   by Rip Stauffer,   Oct 2009  
  "Shewhart soon realized that although there is variation in everything, there are limits to the day-to-day, random variation observed in most processes, and that these limits could be derived statistically. In 1924, he produced the first process control chart, which set the limits of chance variability according to statistical guidelines. The control chart was a brilliant innovation for management, because it indicated when management action could be taken and which types of action would be effective."
  
• Combinatorial Software Testing   by Rick Kuhn, Raghu Kacker, Yu Lei, and Justin Hunter,   Aug 2009  
  While the most basic form of combinatorial testing, pairwise, is well established, and adoption by software testing practitioners continues to increase, industry usage of these methods remains patchy at best. However, the additional training required is well worth the effort. Teams seeking to maximize testing thoroughness given tight time or resource constraints, and which currently rely on manual test case selection methods, should consider pairwise testing. When more time is available or more thorough testing is required, t-way testing for t > 2 is better.
  
• Ten Statisticians and Their Impacts for Psychologists   by Daniel B. Wright,   Jun 2009  
  "I present a list of 10 prominent statisticians: David Cox, Bradley Efron, Ronald Fisher, Leo Goodman, John Nelder, Jerzy Neyman, Karl Pearson, Donald Rubin, Robert Tibshirani, and John Tukey. I then discuss their key contributions and impact for psychology, as well as some aspects of their nonacademic lives."
  
• Control Charting Seasonal Data   by Lynda Finn,   Mar 2009  
  How to create a control chart for seasonal or trending data where there is an underlying structural variation in the data. Essentially you need to account for the structural variation to create the control limits for the control chart.
  
• Practical Combinatorial Testing: Beyond Pairwise   by Rick Kuhn, Yu Lei and Raghu Kacker,   Jun 2008  
  "Within the NASA database application, for example, 67 percent of the failures were triggered by only a single parameter value, 93 percent by two-way combinations, and 98 percent by three-way combinations. The detection-rate curves for the other applications studied are similar, reaching 100 percent detection with four- to six-way interactions."
  
• Performance Measures and Statistics Course Materials   by Steven Prevette,   Dec 2006  
  Course material from a 2 day course. Topics include: Dr. Demings red bead experiment, operational definitions, selecting performance targets, SPC, theory of variation, control charts, pdsa, pareto charts.
  
• Some Comments on Historical Designed Experiments   by Keith M. Bower,   Nov 2004  
  "I wanted to summarize some of the key reasons when and why such an approach would be statistically invalid, and this was the resulting paper. The concept of removing datapoints to 'get the software to work' was something I was very keen to address in the paper - i.e. it is wholly inappropriate."
  
• Dangers of Forgetting the Proxy Nature of Data   by John Hunter,   Aug 2004  
  "We use data to act as a proxy for some results of the system. Often people forget that the desired end result is not for the number to be improved but for the situation to be improved. We hope, if the measure improves the situation will have improved. But there are many reasons this may not be the case (one number improving at the expense of other parts of the system, the failure of the number to accurately serve as a proxy, distorting numbers, etc.)."
  
• Some Survey Guidelines   by George Chynoweth, PhD,   Jan 2004  
  "Balancing Respondent Burden and Organizational Requirements." and "It's all about strategy, or more appropriately, actionable information."
  
• William G. Hunter: An Innovator and Catalyst for Quality Improvement   by George Box,   Nov 2002  
  This is the text of a talk given at the Speakers' Dinner at the Sixth Annual William G. Hunter Conference on Quality in Madison, Wisconsin, on June 2, 1993. In it, George Box recalls Bill Hunter's pivotal role in the birth of the quality movement in the city of Madison. Without Hunter's catalytic contributions, Madison would not have its current leadership position in the improvement of quality in government, industry, and education.
  
• What Can You Find Out From 12 Experimental Runs?   by George Box and Soren Bisgaard,   Nov 2002  
  Examines the possibilities of factorialy designed experiments using many variables at once.
  
• Design Of Experiment For Software Testing   by Madhav S. Phadke,   Nov 2002  
  "Use of orthogonal array based testing has demonstrated to produce superior test plans that improve testing productivity by a factor of 2. This method is found effective in testing the incremental work done in all stages of software development. These stages include writing requirements, selecting architecture, designing the system (functional breakdown), unit testing, platform testing, integration testing, prototype testing, and system testing."
  
• Introduction to Statistical Experimental Design   by Johan Trygg and Svante Wold,   Aug 2002  
  "Statistical experimental design, a.k.a. design of experiments (DoE) is the methodology of how to conduct and plan experiments in order to extract the maximum amount of information in the fewest number of runs"
  
• Three Romeos and a Juliet: - Our early brush with Design of Experiments   by Ravindra Khare,   Jul 2002  
  Very easy to understand explanation of 3 factorial designed experiment. Defeinately no math or statistics knowledge needed.
  
• Statistics for Discovery   by George E. P. Box ,   Mar 2002  
  This report explores why investigators in engineering and the physical sciences rarely use statistics. It is argued that statistics has been overly influenced by mathematical methods rather than the scientific method and consequent the subject has been greatly skewed towards testing rather than discovery.
  
• How to Institute DOE in Your Company   by Al Corwin,   Sep 1999  
  "DOE works, but I don't need to sell that to the readers of this newsletter. But as certain as we all are, no one can deny that design of experiments faces resistance even in environments where it is a proven tool. Every research scientist or engineer who has had a major success from DOE can tell you story after story of how management still wanted problems solved one-factor-at-a-time."
  
• Statistics as a Catalyst to Learning by Scientific Method   by George Box,   Jun 1999  
  Explores the implications raised when Response Surface Methodology (RSM) is considered, as was originally intended as a statistical technique for the catalysis of iterative learning.
  
• A Personal Story of DOE   by Bill Kappele,   Feb 1999  
  "Back in the lab, I tackled ink with DOE. I was able to perform a small number of experiments and learn about interactions among the ingredients. I could see which ingredients appeared to be the most important, which ingredients interacted, and which interactions were most important. This really was a powerful technique."
  
• Software Testing by Statistical Methods   by David Banks et. al.,   Mar 1998  
  "The goal of this work is to ensure software quality and to develop methods for software conformance testing based on known statistical techniques, including multivariable analysis, design of experiments, coverage designs, usage models, and optimization techniques,"
  
• Applying DOE to Microwave Popcorn   by Mark Anderson and Hank Anderson,   Feb 1998  
  "Our DOE on microwave popcorn unintentionally turned out to be a destructive test. The heat and smoke generated at the upper limits of time and power degraded the chamber to a point where we decided it might be best to get a new machine."
  
• Design of Experiments: An Overview and Application Example   by John S. Kim and James W. Kalb,   Mar 1996  
  "DOE techniques are not new to the health-care industry. Medical researchers have long understood the importance of carefully designed experiments. These techniques, however, have not been applied as rigorously in the product and design phases as in the clinical evaluation phase of product development."
  
• Importance of Graphics in Problem Solving and Detective Work   by Soren Bisgaard ,   Feb 1996  
  This article discusses how statistical graphics catalyzes the problem solving process. Two industrial examples are used to illustrate this idea. Center for Quality and Productivity Improvement at the University of Wisconsin-Madison
  
• Managing Our Way to Economic Success: Two Untapped Resources   by William G. Hunter,   Feb 1996  
  "American organizations could compete much better at home and abroad if they would learn to tap the potential information inherent in all processes and the creativity inherent in all employees."
  
• What Can You Find Out From 8 and 16 Experimental Runs?   by George Box,   Feb 1992  
  Includes two articles on options for designed experiments. Design of Experiments is a tools used heavily in Six Sigma programs.
  
• Teaching Engineers Experimental Design With a Paper Helicopter   by George Box,   Dec 1991  
  How a helicopter (made in with a regular sheet of paper) can be used to teach principles of experimental design including - conditions for validity of experimentation, randomization, blocking, the use of factorial and fractional factorial designs, and the management of experimentation.
  
• An Explanation and Critique of Taguchi's Contributions to Quality Engineering   by George Box, Soren Bisgaard, and Conrad Fung,   Mar 1988  
  "This paper presents an overview of Professor Genichi Taguchi's contributions and concludes that Professor Taguchi's quality engineering ideas are of great importance. However, many of the statistical design and analysis techniques he employs are often inefficient and unnecessarily complicated and should be replaced or appropriately modified."
  
• The Scientific Context of Quality Improvement   by George Box and Soren Bisgaard,   Sep 1987  
  Scientific method is a key ingredient in the new philosophy of quality and productivity improvement. This paper provides an overview. A discussion of new ideas of how to design quality into products and processes is provided and Taguchi's work is evaluated and put in context. Publication: Quality Progress, June 1987.
  
• Guinness, Gosset, Fisher, and Small Samples   by Joan Fisher Box,   Feb 1987  
  "The environment in which W. S. Gosset (Student) worked as a brewer at Guinness' Brewery at the turn of the century is described fully enough to show how it forced him to confront problems of small sample statistics, using the techniques he picked up from Karl Pearson. R. A. Fisher's interest in human genetics prompted biometrical applications of his mathematical training even as an undergraduate. As soon as he considered Student's work, he perceived its importance and began to extend its applications"
  
• Studies in Quality Improvement: Designing Environmental Regulations   by Soren Bisgaard and William G. Hunter,   Feb 1986  
  "this report outlines a framework, which is based upon statistical quality control concepts, for designing environmental regulations... With slight modifications, the framework outlined in this report can be applied to the design of standards of all kinds"
  
• The Next 25 Years in Statistics   by William Hill and William Hunter,   Feb 1986  
  (with contributions by Joseph W. Duncan, A. Blanton Godfrey, Brian L. Joiner, Gary C. McDonald, Charles G. Pfeifer, Donald W. Marquardt, and Ronald D. Snee). A transformation of the American style of management has already begun; in order for it to succeed, statisticians must assume a leadership role. Publication(s): Chance, 1990,
  
• Studies in Quality Improvement: Dispersion Effects from Fractional Designs   by George Box and R. Daniel Meyer,   Feb 1986  
  "The expense of repeating measurements can sometimes be avoided by using unreplicated fractional factorials to identify factors that affect dispersion."
  
• 101 Ways to Design an Experiment, or Some Ideas About Teaching Design of Experiments   by William G. Hunter,   Jun 1975  
  A great article sharing ideas on teaching and learning about Design of Experiments (DoE), a powerful and greatly underutilized tool. 6 simga efforts have greatly increased the use of DoE.
  
• Student   by RA Fisher,   Jan 1939  
  Paper by the great Ronald Aylmer Fisher
  
• A Useful Method for Model-Building II: Synthesizing Response Functions from Individual Components   by William G. Hunter and Andrzej P. Jaworski,   Nov 0002  
  "Analyzing which components of a response are due to each factor is an alternative way to find the best model for studying the properties of a product or process (and thus for improving both)." Published in Technometrics.
  
• Variation, Management and W. Edwards Deming   by Brian Joiner and Marie Gaudard,   Nov 0002  
  Originally published in Quality Progress, December 1990. Excellent article.
  

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