Beyond the T-Test - Pardo, Scott A.

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Résumé :
This book was inspired by years of questions asked by non-statistical professionals, from social scientists, public policy analysts, regulatory affairs specialists, engineers, and physical scientists. It provides them with both an intuitive explanation of many common statistical methods and enough mathematical background to help them justify those methods to others, such as regulatory agencies. It provides an introduction to commonly used methods that are not covered in a first elementary statistics course, such as partial least squares, MCMC, and neural networks. It also provides R code for making all the computations described in the text. As a textbook, it could be used as a second course in statistics for non-statisticians, in fields such as social sciences, public policy, engineering, chemistry, and physics. Many first-year graduate students have had an elementary statistics course, but were not exposed to enough of the mathematics to justify the application of those methods. Furthermore, they often encounter methods and concepts not touched upon in their first statistics course. This book provides the tools required to give a deeper understanding of statistical methods without being all about theorems and proofs....

Biographie:
Scott Pardo has been applying statistical methods to a wide variety of problems, from military communications networks to pacemaker longevity to pharmacokinetics to injection molding of syringes, for over 40 years. He has spent most of the last 32 years working in the medical device industries, including pacemakers, in-vitro diagnostics, and blood collection tubes. He has written several books on various statistical topics, including Equivalence Testing in Engineering and Problems in Behavioral Ecology (Springer). Dr. Pardo has a Ph.D. in Industrial Engineering (Engineering Statistics) from the University of Southern California, and is a Six Sigma Master Black Belt. He is the author of Equivalence and Noninferiority Testing for Quality, Manufacturing, and Test Engineers, Empirical Modeling and Data Analysis for Engineers and Applied Scientists, Statistical Methods for Field and Laboratory Studies in Behavioral Ecology and Statistical Analysisof Empirical Data: Methods for Applied Sciences....

Sommaire:
This book was inspired by years of questions asked by non-statistical professionals, from social scientists, public policy analysts, regulatory affairs specialists, engineers, and physical scientists. It provides them with both an intuitive explanation of many common statistical methods and enough mathematical background to help them justify those methods to others, such as regulatory agencies. It provides an introduction to commonly used methods that are not covered in a first elementary statistics course, such as partial least squares, MCMC, and neural networks. It also provides R code for making all the computations described in the text. As a textbook, it could be used as a second course in statistics for non-statisticians, in fields such as social sciences, public policy, engineering, chemistry, and physics. Many first-year graduate students have had an elementary statistics course, but were not exposed to enough of the mathematics to justify the application of those methods. Furthermore, they often encounter methods and concepts not touched upon in their first statistics course. This book provides the tools required to give a deeper understanding of statistical methods without being all about theorems and proofs....