Statistical Consulting

Front Cover
Springer New York, Jan 2, 2002 - Mathematics - 390 pages
The motivation for this book arose from the statistical consulting course that we have taught regularly for several years. In that course, we focus on the themes: • Understanding the statistical consulting "process" • Developing effective communication skills • Obtaining experience through case studies. In reality, there is no substitute for consulting directly with a client and for this interaction to be effective, good communication skills are essential. Unfortunately, this aspect of a statistician's training is often neglected and statistics graduates have little choice but to learn these skills on the job. One of the purposes of this book is to address this need. Statistical consulting occurs in a diverse range of environments and for tackling real-life statistical problems, the statistician needs to have a strong interest in the scientific method. History itself provides the best examples for developing this interest and so we begin with a brief historical voyage in Chapter 1. There's no time like the present, of course, and in the remainder of this chapter we describe some of the environments in which statistical consulting plays a major role. A detailed discussion on verbal and written communication skills that will be required in a consulting environment is presented in Chapter 2.

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About the author (2002)

DHAMMIKA AMARATUNGA, PhD, is a Senior Research Fellow in the Nonclinical Biostatistics Department at Johnson & Johnson Pharmaceutical Research & Development, LLC. He has a doctorate in statistics from Princeton University and has been working in the pharmaceutical industry for over fifteen years. His research interests include analysis of large multivariate data sets, particularly those generated by functional genomics research, robust and resistant statistical methods, linear and nonlinear modeling, and biostatistics.

JAVIER CABRERA, PhD, is an Associate Professor in the Department of Statistics at Rutgers University. He has a doctorate in statistics from Princeton University and has over fifty publications in applied statistics. His research interests include DNA microarray, data mining of biopharmaceutical databases, computer vision, statistical computing and graphics, robustness, and biostatistics.