Statistical thinking is pervasive in all disciplines engaged in empirical inquiry. The purpose of Statistical Science is to develop methods for designing and analyzing such inquiries, and to disseminate this methodology through teaching and scholarly communication.
Development of useful statistical methodology cannot take place in a vacuum. To be scientifically relevant this development should be problem-driven, motivated and guided by applications of scientific importance. Identifying and understanding important applications requires interaction with other disciplines that acquire and analyze data. Collaborative research is therefore essential to the viability and growth of Statistics.
While mathematics provides the machinery for theoretical analysis of statistical procedures, Statistics is not a subfield of Mathematics. In the last 20 years, data collection and data analysis have been transformed by the computer revolution. Computers have made it feasible to collect large data sets (gigabytes of information). The pervasiveness of computers in daily life brought on by services such as the Web and Internet shopping is giving rise to entirely new data sources and data types. Computers also have tremendously expanded the range of statistical tools that can be implemented in practice. The Bootstrap, nonparametric prediction methods like CART and Neural Networks, the Cox model for survival analysis, The Grand Tour and scatterplot painting for data visualization, Bayesian networks and graphical Markov models, and Markov Chain Monte Carlo would have been unthinkable without the advances in computing.
Demand is rapidly increasing for new data analytic tools, and for individuals trained to invent, evaluate, and apply them. The increasing importance of computers in both data collection and data analysis has made expertise in computing an important prerequisite for creating and applying new and innovative data analysis tools. Computer Science is approaching a position on par with Mathematics as a foundation for Statistics. In order to live at the cutting edge of data analysis, statisticians must account for this paradigm shift in their research and teaching.
At the time of the establishment of the Department of Statistics at the University of Washington in 1979, the Departments of Mathematics and Biostatistics already had strong and thriving programs in probability theory, mathematical statistics, and statistical applications. The Statistics Department dedicated itself to further strengthening these areas while developing new expertise in the emerging and important area of computer-intensive statistical methodology. Collaborative, cross-disciplinary research was also emphasized and continues to be a distinguishing feature of its academic program. The recently established Northwest Research Center for Statistics and the Environment (NRCSE), the Center for Statistics and the Social Sciences (CSSS), and the Statistical Genetics (StatGen) program provide exciting new research opportunities for both faculty and graduate students.