ABSTRACT
This introduction presents an overview of the key concepts discussed in the subsequent chapters of this book. The book describes some of the more interesting and promising areas of statistical computation, and discusses the breadth that is possible in the area. It demonstrates that successful work in statistical computation broadly understood requires a broad background both in classical and modern statistics and in classical and modern computer science. The book provides the kinds of computational concerns into six overlapping categories: numerical, seminumerical, graphical, symbolic, environmental, and theoretical. It argues that a broader view of statistics can be beneficial in constructing certain kinds of expert systems. The book describes some history of the interactions between data analysts and digital computers. Statistical computing has been part of statistical methods largely through algorithms implementing the computation of standard quantities.
