An incomparably useful examination of statistical methods for comparison
The nature of doing science, be it natural or social, inevitably calls for comparison. Statistical methods are at the heart of such comparison, for they not only help us gain understanding of the world around us but often define how our research is to be carried out. The need to compare between groups is best exemplified by experiments, which have clearly defined statistical methods. However, true experiments are not always possible. What complicates the matter more is a great deal of diversity in factors that are...

While mapped data provide a common ground for discussions between the public, the media, regulatory agencies, and public health researchers, the analysis of spatially referenced data has experienced a phenomenal growth over the last two decades, thanks in part to the development of geographical information systems (GISs). This is the first thorough overview to integrate spatial statistics with data management and the display capabilities of GIS. It describes methods for assessing the likelihood of observed patterns and quantifying the link between exposures and outcomes in spatially...

Designed to help motivate the learning of advanced calculus by demonstrating its relevance in the field of statistics, this successful text features detailed coverage of optimization techniques and their applications in statistics while introducing the reader to approximation theory. The Second Edition provides substantial new coverage of the material, including three new chapters and a large appendix that contains solutions to almost all of the exercises in the book. Applications of some of these methods in statistics are discusses.

The most comprehensive, single-volume guide to conducting experiments with mixtures

"If one is involved, or heavily interested, in experiments on mixtures of ingredients, one must obtain this book. It is, as was the first edition, the definitive work."
-Short Book Reviews (Publication of the International Statistical Institute)

"The text contains many examples with worked solutions and with its extensive coverage of the subject matter will prove invaluable to those in the industrial and educational sectors whose work involves the design and analysis of mixture...

The new edition adds a chapter on multiple linear regression in biomedical research, with sections including the multiple linear regressions model and least squares; the ANOVA table, parameter estimates, and confidence intervals; partial f-tests; polynomial regression; and analysis of covariance.
* Organized by problem rather than method, so it guides readers to the correct technique for solving the problem at hand.

Accessible to medicine- and/or public policy-related audiences, as well as most statisticians.

• Emphasis on outliers is discussed by way of detection and treatment.
• Resampling statistics software is incorporated throughout.
• Motivating applications are presented in light of honest theory.
• Plentiful exercises are sprinkled throughout.

Introducing a groundbreaking companion book to a bestselling reliability text

Reliability is one of the most important characteristics defining the quality of a product or system, both for the manufacturer and the purchaser. One achieves high reliability through careful monitoring of design, materials and other input, production, quality assurance efforts, ongoing maintenance, and a variety of related decisions and activities. All of these factors must be considered in determining the costs of production, purchase, and ownership of a product.

Case Studies in Reliability...

This 3rd edition of the successful Elements of Applied Stochastic Processes improves on the last edition by condensing the material and organising it into a more teachable format. It provides more in-depth coverage of Markov chains and simple Markov process and gives added emphasis to statistical inference in stochastic processes.

• Integration of theory and application offers improved teachability
• Provides a comprehensive introduction to stationary processes and time series analysis
• Integrates a broad set of applications into the text
• Utilizes a...

Concise, mathematically clear, and comprehensive treatment of the subject.
* Expanded coverage of diagnostics and methods of model fitting.
* Requires no specialized knowledge beyond a good grasp of matrix algebra and some acquaintance with straight-line regression and simple analysis of variance models.
* More than 200 problems throughout the book plus outline solutions for the exercises.
* This revision has been extensively class-tested.

Longitudinal data analysis for biomedical and behavioral sciences

This innovative book sets forth and describes methods for the analysis of longitudinaldata, emphasizing applications to problems in the biomedical and behavioral sciences. Reflecting the growing importance and use of longitudinal data across many areas of research, the text is designed to help users of statistics better analyze and understand this type of data.

Much of the material from the book grew out of a course taught by Dr. Hedeker on longitudinal data analysis. The material is, therefore,...