Steven P. Millard - Böcker

A clear, comprehensive treatment of the subject, Environmental Statistics with S-PLUS surveys the vast array of statistical methods used to collect and analyze environmental data. The book explains what these methods are, how to use them, and where to find references to them. In addition, it provides insight into what to think about before you collect environmental data, how to collect the data, and how to make sense of it after collection.A unique and powerful feature of the book is its integration with the commercially available software package S-Plus and the add-on modules EnvironmentalStats for S-PLUS, S+SpatialStats, and S-PLUS for ArcView. The book presents data sets to explain statistical methods, and then shows how to implement these methods by providing the commands for and the results from the software.This survey of statistical methods, definitions, and concepts helps you collect and effectively analyze data for environmental pollution problems. Using the S-PLUS software in conjunction with this text will no doubt increase understanding of the methods.

The purpose of this book is to provide a general guide to statistical methods used in the pharmaceutical industry, and to illustrate how to use S-PLUS to implement these methods. Specifically, the goal is to: *Illustrate statistical applications in the pharmaceutical industry; *Illustrate how the statistical applications can be carried out using S-PLUS; *Illustrate why S-PLUS is a useful software package for carrying out these applications; *Discuss the results and implications of a particular application; The target audience for this book is very broad, including: *Graduate students in biostatistics; *Statisticians who are involved in the industry as research scientists, regulators, academics, and/or consultants who want to know more about how to use S-PLUS and learn about other sub-fields within the indsutry that they may not be familiar with; *Statisticians in other fields who want to know more about statistical applications in the pharmaceutical industry.

A clear, comprehensive treatment of the subject, Environmental Statistics with S-PLUS surveys the vast array of statistical methods used to collect and analyze environmental data. The book explains what these methods are, how to use them, and where to find references to them. In addition, it provides insight into what to think about before you collect environmental data, how to collect the data, and how to make sense of it after collection.A unique and powerful feature of the book is its integration with the commercially available software package S-Plus and the add-on modules EnvironmentalStats for S-PLUS, S+SpatialStats, and S-PLUS for ArcView. The book presents data sets to explain statistical methods, and then shows how to implement these methods by providing the commands for and the results from the software.This survey of statistical methods, definitions, and concepts helps you collect and effectively analyze data for environmental pollution problems. Using the S-PLUS software in conjunction with this text will no doubt increase understanding of the methods.

The purpose of this book is to provide a general guide to statistical methods used in the pharmaceutical industry, and to illustrate how to use S-PLUS to implement these methods. Specifically, the goal is to: *Illustrate statistical applications in the pharmaceutical industry; *Illustrate how the statistical applications can be carried out using S-PLUS; *Illustrate why S-PLUS is a useful software package for carrying out these applications; *Discuss the results and implications of a particular application; The target audience for this book is very broad, including: *Graduate students in biostatistics; *Statisticians who are involved in the industry as research scientists, regulators, academics, and/or consultants who want to know more about how to use S-PLUS and learn about other sub-fields within the indsutry that they may not be familiar with; *Statisticians in other fields who want to know more about statistical applications in the pharmaceutical industry.