Nov 252016
 

Introduction to Statistics for Forensic Scientists


By (author): David Lucy

Introduction to Statistics for Forensic Scientists is an essential introduction to the subject, gently guiding the reader through the key statistical techniques used to evaluate various types of forensic evidence. Assuming only a modest mathematical background, the book uses real-life examples from the forensic science literature and forensic case-work to illustrate relevant statistical concepts and methods.

Opening with a brief overview of the history and use of statistics within forensic science, the text then goes on to introduce statistical techniques commonly used to examine data obtained during laboratory experiments. There is a strong emphasis on the evaluation of scientific observation as evidence and modern Bayesian approaches to interpreting forensic data for the courts. The analysis of key forms of evidence are discussed throughout with a particular focus on DNA, fibres and glass.

An invaluable introduction to the statistical interpretation of forensic evidence; this book will be invaluable for all undergraduates taking courses in forensic science.

  • Introduction to the key statistical techniques used in the evaluation of forensic evidence
  • Includes end of chapter exercises to enhance student understanding
  • Numerous examples taken from forensic science to put the subject into context
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Nov 232016
 

Statistical Applications from Clinical Trials and Personalized Medicine to Finance and Business Analytics: Selected Papers from the 2015 ICSA/Graybill … Fort Collins (ICSA Book Series in Statistics)


The papers in this volume represent a broad, applied swath of advanced contributions to the 2015 ICSA/Graybill Applied Statistics Symposium of the International Chinese Statistical Association, held at Colorado State University in Fort Collins.  The contributions cover topics that range from statistical applications in business and finance to applications in clinical trials and biomarker analysis.  Each papers was peer-reviewed by at least two referees and also by an editor.  The conference was attended by over 400 participants from academia, industry, and government agencies around the world, including from North America, Asia, and Europe.
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Nov 122016
 

Tools for Statistical Inference: Observed Data and Data Augmentation Methods (Lecture Notes in Statistics)


By (author): Martin A. Tanner

From the reviews: The purpose of the book under review is to give a survey of methods for the Bayesian or likelihood-based analysis of data. The author distinguishes between two types of methods: the observed data methods and the data augmentation ones. The observed data methods are applied directly to the likelihood or posterior density of the observed data. The data augmentation methods make use of the special “missing” data structure of the problem. They rely on an augmentation of the data which simplifies the likelihood or posterior density. #Zentralblatt für Mathematik#
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Nov 102016
 

Medical Statistics: For Beginners


By (author): Ramakrishna HK

This book deals with statistics in medicine in a simple way. The text is supported by abundant examples from medical data. This book aims to explain and simplify the process of data presentation. Further aspects addressed include how to design and conduct clinical trials, and how to write journal articles. 
 
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Nov 052016
 

Thrombosis and Embolism: from Research to Clinical Practice: Volume 1 (Advances in Experimental Medicine and Biology)


This unique publication explores diverse themes relating to thrombosis and embolism, from basic research at cell and molecular level to the actual care, prevention, and treatment of diverse categories of patients suffering from such diseases. Chapters cover a variety of topics including thrombosis and embolism in surgical patients, cancer patients, pregnant women and children and adolescents, as well as treatment of the conditions by traditional anticoagulants, novel oral anticoagulants, thrombolytic therapy, endovascular treatment and embolectomy. Readers may explore cutting edge research, recommendations from major societies, contemporary guidelines, areas of controversy and directions for ongoing and future research.

The book features comprehensive information ranging from molecular mechanisms of diseases to the clinical features, diagnosis, and therapeutic regimens for treating a variety of clinical conditions. It has a broad appeal to scientists and research students as well as busy clinicians engaged in patient care, who will all find something important and useful amongst these carefully selected chapters. 

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Nov 052016
 

New Developments in Statistical Modeling, Inference and Application: Selected Papers from the 2014 ICSA/KISS Joint Applied Statistics Symposium in Portland, OR (ICSA Book Series in Statistics)


The papers in this volume represent the most timely and advanced contributions to the 2014 Joint Applied Statistics Symposium of the International Chinese Statistical Association (ICSA) and the Korean International Statistical Society (KISS), held in Portland, Oregon. The contributions cover new developments in statistical modeling and clinical research: including model development, model checking, and innovative clinical trial design and analysis. Each paper was peer-reviewed by at least two referees and also by an editor. The conference was attended by over 400 participants from academia, industry, and government agencies around the world, including from North America, Asia, and Europe. It offered 3 keynote speeches, 7 short courses, 76 parallel scientific sessions, student paper sessions, and social events.
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Nov 032016
 

Statistical Learning from a Regression Perspective (Springer Texts in Statistics)


Features: Statistical Learning from a Regression Perspective Springer Texts in Statistics
By (author): Richard A. Berk

This textbook considers statistical learning applications when interest centers on the conditional distribution of the response variable, given a set of predictors, and when it is important to characterize how the predictors are related to the response. 
This fully revised new edition includes important developments over the past 8 years. Consistent with modern data analytics, it emphasizes that a proper statistical learning data analysis derives from sound data collection, intelligent data management, appropriate statistical procedures, and an accessible interpretation of results. As in the first edition, a unifying theme is supervised learning that can be treated as a form of regression analysis. Key concepts and procedures are illustrated with real applications, especially those with practical implications. 
The material is written for upper undergraduate level and graduate students in the social and life sciences and for researchers who want to apply statistical learning procedures to scientific and policy problems. The author uses this book in a course on modern regression for the social, behavioral, and biological sciences. All of the analyses included are done in R with code routinely provided.
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Nov 032016
 

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Oct 292016
 

Medical Translation Step by Step: Learning by Drafting (Translation Practices Explained)


Features: Routledge
By (author): Vicent Montalt, Maria González-Davies

Statistics on the translation market consistently identify medicine as a major thematic area as far as volume or translation is concerned. Vicent Montalt and Maria Gonzalez Davis, both experienced translator trainers at Spanish universities, explain the basics of medical translation and ways of teaching and learning how to translate medical texts.

Medical Translation Step by Step provides a pedagogical approach to medical translation based on learner and learning-centred teaching tasks, revolving around interaction: pair and group work to carry out the tasks and exercises to practice the points covered. These include work on declarative and operative knowledge of both translation and medical texts and favour an approach that takes into account both the process and product of translations. Starting from a broad communication framework, the book follows a top-down approach to medical translation: communication ? genres ? texts ? terms and other units of specialized knowledge. It is positively focused in that it does not insist on error analysis, but rather on ways of writing good translations and empowering both students and teachers.

The text can be used as a course book for students in face-to-face learning, but also in distance and mixed learning situations. It will also be useful for teachers as a resource book, or a core book to be complemented with other materials.

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Oct 262016
 

Clinical Trial Data Analysis Using R (Chapman & Hall/CRC Biostatistics Series)


Features: Used Book in Good Condition
By (author): Ding-Geng (Din) Chen, Karl E. Peace

Too often in biostatistical research and clinical trials, a knowledge gap exists between developed statistical methods and the applications of these methods. Filling this gap, Clinical Trial Data Analysis Using R provides a thorough presentation of biostatistical analyses of clinical trial data and shows step by step how to implement the statistical methods using R. The book’s practical, detailed approach draws on the authors’ 30 years of real-world experience in biostatistical research and clinical development.

Each chapter presents examples of clinical trials based on the authors’ actual experiences in clinical drug development. Various biostatistical methods for analyzing the data are then identified. The authors develop analysis code step by step using appropriate R packages and functions. This approach enables readers to gain an understanding of the analysis methods and R implementation so that they can use R to analyze their own clinical trial data.

With step-by-step illustrations of R implementations, this book shows how to easily use R to simulate and analyze data from a clinical trial. It describes numerous up-to-date statistical methods and offers sound guidance on the processes involved in clinical trials.

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