A management consulting view on the statistical consulting process

In an earlier contribution to this journal, Kauermann and Weihs (Adv. Stat. Anal. 91(4):344 2007) addressed the lack of procedural understanding in statistical consulting: “Even though there seems to be a consensus that statistical consulting should be well structured and target-orientated, the range of activity and the process itself seem to be less well-understood.” While this issue appears to be rather new to statistical consultants, other consulting disciplines—in particular management consultants—have long come up with a viable approach that divides the typical consulting process into seven successive steps. Using this model as a frame allows for reflecting the approaches on statistical consulting suggested by authors published in AStA volume 91, number 4, and for adding value to statistical consulting in general.     

An expert system for statistical consulting

The authors have developed an expert system for the analysis of variance to provide guidance to the data analyst on preparing data, selecting statistical methods and choosing computer programs. This system queries the user on the type of data, sampling method and design considerations. It then suggests an appropriate analysis of variance routine and statistical package. The system provides help in understanding the computer output and with model evaluation. The primary user is a scientist with some knowledge of statistics. This system gives the user easy access to statistical expertise and frees the consultant from some important but routine tasks. It may also be a tool to train users and statistical consultants. A significant benefit of this exercise was an increased understanding of the statistical strategies used by consultants and the complexity of the statistical consulting process between humans. This paper will focus on the problem formulation, acquisition of the knowledge base, the model structure and educational benefits.     

Providing Consulting Experiences Through Role Playing in a Graduate Statistics Course

An effective method for improving the communication skills of graduate students in statistics and biostatistics is to provide consultations with non‐statistical researchers. Unfortunately, those experiences can be difficult to arrange or occur too infrequently to be reliable. The current study sought to help students develop both written and oral communication skills within an existing graduate biostatistics course by having students partake in role‐playing consultations. Though the class size was small, the students felt these activities helped improve their oral and written communication skills, and made them more aware of a biostatistician's role in consulting. There was also modest improvement in the students perceived function as a consulting biostatistician. Simulated consultations can be an effective educational tool for promoting the development of soft skills necessary for developing successful statisticians, can be implemented in existing courses, and do not require reliance upon external collaborators. Embedding these types of exercises within an existing curriculum can also be a cost‐effective alternative for programs that do not have formal consulting training.     

Response

This article focuses on the roles consulting units can play in statistics departments, universities, and the statistics profession. An opinion on what constitutes legitimate academic activity is given. The roles endorsed are consistent with the view that statistics is both a science and an integral part of scientific methodology and hence that statistics departments need to be concerned with both the development of new methods and the proper application of those methods in the pure and applied sciences. Consulting units serve as an interface between the developers and users of statistical methodology. Communication between developers and users can be carried on effectively through consultants who are actively involved in the education of users and in the education of statistics students, either formally or informally. Such communication is also enhanced when consultants are publishing in both statistics and nonstatistics journals. Routine data analysis is not endorsed as a justifiable academic activity for consulting faculty. Supervision of graduate students on such analyses, however, can be justified. The success a consulting unit can have in playing its roles depends on appropriate funding, staffing, and administration of the unit.     

Enhancing statistical education by using role-plays of consultations

Summary.  Role-plays in which students act as clients and statistical consultants to each other in pairs have proved to be an effective class exercise. As well as helping to teach statistical methodology, they are effective at encouraging statistical thinking, problem solving, the use of context in applied statistical problems and improving attitudes towards statistics and the statistics profession. Furthermore, they are fun. This paper explores the advantages of using role-plays and provides some empirical evidence supporting their success. The paper argues that there is a place for teaching statistical consulting skills well before the traditional post-graduate qualification in statistics, including to school students with no knowledge of techniques in statistical inference.     

Statistical consulting at German universities: Results of a survey

The article presents the results of a survey on statistical consulting at German universities, where the survey focused on obtaining information on when, where and to whom statistical consulting is provided. We investigate the financial frame of the activity and question the advantages and disadvantages from a consultant’s point of view.     

Recent Developments and Their Implications for the Future of Academic Statistical Consulting Centers

I describe how developments over the past 25 years in computing, funding, personnel, purpose, and training have affected academic statistical consulting centers and discuss how these developments and trends point to a range of potential futures. At one extreme, academic statistical consulting centers fail to adapt to competition from other disciplines in an increasingly fragmented market for statistical consulting and spiral downward toward irrelevancy and extinction. At the other extreme, purpose-driven academic statistical consulting centers constantly increase their impact in a virtuous cycle, leading the way toward the profession of statistics having greater positive impact on society. I conclude with actions to take to assure a robust future and increased impact for academic statistical consulting centers.     

Preparing Statisticians for Careers in Industry: Report of the ASA Section on Statistical Education Committee on Training of Statisticians for Industry

This report provides guidelines for universities to consider in developing programs for training statisticians who will work in industry. Useful information for students who are considering industrial employment is also included. The recommended programs focus on real problems and the statistical theory and methodology that are useful in their solution. Technical competence is only one of many factors that industry considers when hiring and promoting statisticians. When a statistician leaves school, his or her skills and experiences should include statistical knowledge, practical problem solving, consulting practice, and the ability to communicate orally and in writing with nonstatisticians. There are many details that must be worked out (e.g., content of specific courses and organization of consulting internship programs), and it is hoped that the statistical societies and universities will form committees, hold conferences, and develop programs to address these issues further. Many of our recommendations apply more broadly to the training of all types of practicing statisticians.     

LogXact 4.1 for Windows

Box's paper helicopter has been used to teach experimental design for more than a decade. It is simple, inexpensive, and provides real data for an involved, multifactor experiment. Unfortunately it can also further an all-too-common practice that Professor Box himself has repeatedly cautioned against, namely ignoring the fundamental science while rushing to solve problems that may not be sufficiently understood. Often this slighting of the science so as to get on with the statistics is justified by referring to Box's oft-quoted maxim that “All models are wrong, however some are useful.” Nevertheless, what is equally true, to paraphrase both Professor Box and George Orwell, is that “All models are wrong, but some are more wrong than others.” To experiment effectively it is necessary to understand the relevant science so as to distinguish between what is usefully wrong, and what is dangerously wrong.

This article presents an improved analysis of Box's helicopter problem relying on statistical and engineering knowledge and shows that this leads to an enhanced paper helicopter, requiring fewer experimental trails and achieving superior performance. In fact, of the 20 experimental trials run for validation—10 each of the proposed aerodynamic design and the conventional full factorial optimum—the longest 10 flight times all belong to the aerodynamic optimum, while the shortest 10 all belong to the conventional full factorial optimum. I further discuss how ancillary engineering knowledge can be incorporated into thinking about—and teaching—experimental design.     

Planning for the 1950 Censuses of Population and Agriculture

The change from the z of “Student's” 1908 paper to the t of present day statistical theory and practice is traced and documented. It is shown that the change was brought about by the extension of “Student's” approach, by R.A. Fisher, to a broader class of problems, in response to a direct appeal from “Student” for a solution to one of these problems.     

Statistics for Quality and Productivity: A New Graduate-Level Statistics Course

The growing popular realization that American product quality and productivity are no longer without challenge for world leadership presents an opportunity for the American statistical community to make stronger contributions to sound industrial practice than it has in the past. Management consultants, such as Deming and Juran, are promoting philosophies that contain strong statistical components and are being heard by top U.S. executives. There are thus growing opportunities for industrial statisticians. Upon reviewing the content of typical graduate-level statistical quality control courses and books in the light of the present situation, we find them to be inadequate and in some cases to suffer from inappropriate emphases. In this article we discuss our perceptions of what is needed in the way of a new graduate-level course in statistics for quality and productivity (SQP). We further offer for discussion a syllabus for such a course (which is a modification of one used at Iowa State in the 1983 spring semester), some comments on how specific topics might be approached, and also a partially annotated list of references for material that we believe belongs in a modern SQP course.     

A revisit to test the equality of variances of several populations

We revisit the problem of testing homoscedasticity (or, equality of variances) of several normal populations which has applications in many statistical analyses, including design of experiments. The standard text books and widely used statistical packages propose a few popular tests including Bartlett's test, Levene's test and a few adjustments of the latter. Apparently, the popularity of these tests have been based on limited simulation study carried out a few decades ago. The traditional tests, including the classical likelihood ratio test (LRT), are asymptotic in nature, and hence do not perform well for small sample sizes. In this paper we propose a simple parametric bootstrap (PB) modification of the LRT, and compare it against the other popular tests as well as their PB versions in terms of size and power. Our comprehensive simulation study bursts some popularly held myths about the commonly used tests and sheds some new light on this important problem. Though most popular statistical software/packages suggest using Bartlette's test, Levene's test, or modified Levene's test among a few others, our extensive simulation study, carried out under both the normal model as well as several non-normal models clearly shows that a PB version of the modified Levene's test (which does not use the F-distribution cut-off point as its critical value), and Loh's exact test are the “best” performers in terms of overall size as well as power.     

On Teaching Statistical Practice: From Novice to Expert

This article introduces principles of learning based on research in cognitive science that help explain how learning works. We adapt these principles to the teaching of statistical practice and illustrate the application of these principles to the curricular design of a new master's degree program in applied statistics. We emphasize how these principles can be used not only to improve instruction at the course level but also at the program level.     

Statistical consulting

The paper and the special issue focus on the activity of statistical consulting and its varieties. This includes academic consulting, consulting to and in industry as well as statistics in public media.     

The Blind Paper Cutter: Teaching about Variation,Bias, Stability,and Process Control

The intention of this article is to provide teachers with a student activity to help reinforce learning about variation, bias, stability, and other statistical quality control concepts. Blind paper cutting is an effective way of generating tangible sequences of a product, which students can use to address many levels of questions. No special apparatus is required.     

A Note on the Non-equivalence of the Neyman-Pearson and Generalized Likelihood Ratio Tests for Testing a Simple Null versus a Simple Alternative Hypothesis

Despite the great increase in the use of color in statistical graphics, we know very little about how color affects people's perception of the quantitative information on graphical displays. Perceptual psychologists have already demonstrated that color can cause optical illusions of various kinds. We ran a simple experiment to see if this can happen with a statistical map and found that an illusion did occur.     

Theory of optimal blocking of nonregular factorial designs

The authors introduce the notion of split generalized wordlength pattern (GWP), i.e., treatment GWP and block GWP, for a blocked nonregular factorial design. They generalize the minimum aberration criterion to suit this type of design. Connections between factorial design theory and coding theory allow them to obtain combinatorial identities that govern the relationship between the split GWP of a blocked factorial design and that of its blocked consulting design. These identities work for regular and nonregular designs. Furthermore, the authors establish general rules for identifying generalized minimum aberration (GMA) blocked designs through their blocked consulting designs. Finally they tabulate and compare some GMA blocked designs from Hall's orthogonal array OA(16,2¹5,2) of type III.     

RAO'S SCORE TESTS IN SURVIVAL ANALYSIS: EXAMPLES AND BARTLETT TYPE ADJUSTMENTS

Score method in hypothesis testing is one of Professor C. R. Rao's great contributions to statistics. It provides a simple and unified way to test some simple and composite hypotheses in many statistical problems. Some popular tests in statistical practice derived with the help of intuitions can be shown as score tests under some statistical models. The subject-years test and log-rank test in survival analysis are two of the examples. In this paper, we first introduce these two examples. After formulating these two tests as score tests, we then review some recent results on the Bartlett type adjustments for these tests.     

The Many Facets of Statistics Education: 175 Years of Common Themes

The American Statistical Association's primary founder, Lemuel Shattuck, was driven by a passion for collecting and disseminating accurate information on vital statistics, public health, and other statistically related concerns. The 175th anniversary provides an opportunity to reflect on the education-related reasons ASA was founded and what it has done in education since its founding, especially in the past 25 years since the 150th anniversary. An examination of early and more recent issues of the ASA's journals reveals some common themes that have recurred over the past 175 years. We discuss what those themes are and what the ASA is doing to address them currently, and then conclude by discussing what ASA members can do to help.     

Precise definitions of some terminology for longitudinal clinical trials: subjects,patient populations,analysis sets,intention to treat,and related terms

Biostatisticians recognize the importance of precise definitions of technical terms in randomized controlled clinical trial (RCCT) protocols, statistical analysis plans, and so on, in part because definitions are a foundation for subsequent actions. Imprecise definitions can be a source of controversies about appropriate statistical methods, interpretation of results, and extrapolations to larger populations. This paper presents precise definitions of some familiar terms and definitions of some new terms, some perhaps controversial. The glossary contains definitions that can be copied into a protocol, statistical analysis plan, or similar document and customized. The definitions were motivated and illustrated in the context of a longitudinal RCCT in which some randomized enrollees are non‐adherent, receive a corrupted treatment, or withdraw prematurely. The definitions can be adapted for use in a much wider set of RCCTs. New terms can be used in place of controversial terms, for example, subject. We define terms specifying a person's progress through RCCT phases and that precisely define the RCCT's phases and milestones. We define terms that distinguish between subsets of an RCCT's enrollees and a much larger patient population. ‘The intention‐to‐treat (ITT) principle’ has multiple interpretations that can be distilled to the definitions of the ‘ITT analysis set of randomized enrollees’. Most differences among interpretations of ‘the’ ITT principle stem from an RCCT's primary objective (mainly efficacy versus effectiveness). Four different ‘authoritative’ definitions of ITT analysis set of randomized enrollees illustrate the variety of interpretations. We propose a separate specification of the analysis set of data that will be used in a specific analysis. Copyright © 2016 John Wiley & Sons, Ltd.