ABSTRACT
The practicing statistician faces a variety of challenges: designing complex studies, summarizing complex data sets, fitting probability models, drawing conclusions about the present, and making predictions for the future. Statistical studies play an important role in scientific discovery, in policy formulation, and in business decisions. Applications of statistics are ubiquitous, and include clinical decision making, conducting an environmental risk assessment, setting insurance rates, deciding whether (and how) to market a new product, and allocating federal funds. Currently, most statistical analyses are performed with the help of commercial software packages, most of which use methods based on a classical, or frequentist, statistical philosophy. In this framework, maximum likelihood estimates (MLEs) and hypothesis tests based on p-values figure prominently.
