Books in the Statistics in Practice series

Modern Industrial StatisticsThe new edition of the prime reference on the tools of statistics used in industry and services, integrating theoretical, practical, and computer-based approachesModern Industrial Statistics is a leading reference and guide to the statistics tools widely used in industry and services. Designed to help professionals and students easily access relevant theoretical and practical information in a single volume, this standard resource employs a computer-intensive approach to industrial statistics and provides numerous examples and procedures in the popular R language and for MINITAB and JMP statistical analysis software. Divided into two parts, the text covers the principles of statistical thinking and analysis, bootstrapping, predictive analytics, Bayesian inference, time series analysis, acceptance sampling, statistical process control, design and analysis of experiments, simulation and computer experiments, and reliability and survival analysis. Part A, on computer age statistical analysis, can be used in general courses on analytics and statistics. Part B is focused on industrial statistics applications.The fully revised third edition covers the latest techniques in R, MINITAB and JMP, and features brand-new coverage of time series analysis, predictive analytics and Bayesian inference. New and expanded simulation activities, examples, and case studies--drawn from the electronics, metal work, pharmaceutical, and financial industries--are complemented by additional computer and modeling methods. Helping readers develop skills for modeling data and designing experiments, this comprehensive volume:* Explains the use of computer-based methods such as bootstrapping and data visualization* Covers nonstandard techniques and applications of industrial statistical process control (SPC) charts* Contains numerous problems, exercises, and data sets representing real-life case studies of statistical work in various business and industry settings* Includes access to a companion website that contains an introduction to R, sample R code, csv files of all data sets, JMP add-ins, and downloadable appendices* Provides an author-created R package, mistat, that includes all data sets and statistical analysis applications used in the bookPart of the acclaimed Statistics in Practice series, Modern Industrial Statistics with Applications in R, MINITAB, and JMP, Third Edition, is the perfect textbook for advanced undergraduate and postgraduate courses in the areas of industrial statistics, quality and reliability engineering, and an important reference for industrial statisticians, researchers, and practitioners in related fields. The mistat R-package is available from the R CRAN repository.

Statistical complex survey analysis is a means to analyse the results, and gain information about a large population based on a complex survey of a sample of that population. A complex survey is a sample survey that divides the population into subgroups and collecting information from clusters within each subgroup and combining the results.

Features coverage of the epidemiological indices, and includes developments in the field. This title serves as a useful reference source for biostatisticians and epidemiologists working in disease prevention, as the chapters are self-contained and feature several real examples.

Explores computer-intensive probability and statistics for ecosystem management decision making Simulation is an accessible way to explain probability and stochastic model behavior to beginners.

An authoritative introduction to efficiency and productivity analysis with applications in both the banking and finance industry In light of the recent global financial crisis, several studies have examined the efficiency of financial institutions.

A practical guide to network meta-analysis with examples and code In the evaluation of healthcare, rigorous methods of quantitative assessment are necessary to establish which interventions are effective and cost-effective.

Introduces risk assessment with key theories, proven methods, and state-of-the-art applications Risk Assessment: Theory, Methods, and Applications remains one of the few textbooks to address current risk analysis and risk assessment with an emphasis on the possibility of sudden, major accidents across various areas of practice--from machinery and manufacturing processes to nuclear power plants and transportation systems. Updated to align with ISO 31000 and other amended standards, this all-new 2nd Edition discusses the main ideas and techniques for assessing risk today. The book begins with an introduction of risk analysis, assessment, and management, and includes a new section on the history of risk analysis. It covers hazards and threats, how to measure and evaluate risk, and risk management. It also adds new sections on risk governance and risk-informed decision making; combining accident theories and criteria for evaluating data sources; and subjective probabilities. The risk assessment process is covered, as are how to establish context; planning and preparing; and identification, analysis, and evaluation of risk. Risk Assessment also offers new coverage of safe job analysis and semi-quantitative methods, and it discusses barrier management and HRA methods for offshore application. Finally, it looks at dynamic risk analysis, security and life-cycle use of risk. Serves as a practical and modern guide to the current applications of risk analysis and assessment, supports key standards, and supplements legislation related to risk analysis Updated and revised to align with ISO 31000 Risk Management and other new standards and includes new chapters on security, dynamic risk analysis, as well as life-cycle use of risk analysis Provides in-depth coverage on hazard identification, methodologically outlining the steps for use of checklists, conducting preliminary hazard analysis, and job safety analysis Presents new coverage on the history of risk analysis, criteria for evaluating data sources, risk-informed decision making, subjective probabilities, semi-quantitative methods, and barrier management Contains more applications and examples, new and revised problems throughout, and detailed appendices that outline key terms and acronyms Supplemented with a book companion website containing Solutions to problems, presentation material and an Instructor Manual Risk Assessment: Theory, Methods, and Applications, Second Edition is ideal for courses on risk analysis/risk assessment and systems engineering at the upper-undergraduate and graduate levels. It is also an excellent reference and resource for engineers, researchers, consultants, and practitioners who carry out risk assessment techniques in their everyday work.

Modeling and Analysis of Compositional Data presents a practical and comprehensive introduction to the analysis of compositional data along with numerous examples to illustrate both theory and application of each method.

There has been substantial growth in the use of data monitoring committees in recent years, particularly within the pharmaceutical industry. This growth has brought with it increasing uncertainty regarding regulatory compliance, and the statistician or clinical trials co-ordinator often has to struggle with conflicting information.

Selection bias can, and does, occur, even in randomized clinical trials. Steps need to be taken in order to ensure that this does not compromise the integrity of clinical trials; hence "Selection Bias and Covariate Imbalances in Randomized Clinical Trials" offers a comprehensive treatment of the subject and the methodology involved.

Covers practical and fundamental aspects of environmental statistics.

Meta--analysis is one of the main statistical methods used in clinical trials. Previous accounts of meta--analysis have given the impression that the topic is a series of separate techniques. This book provides a unified approach, developing the subject from mathematical theory through to practical discussions of implementation.

Disease mapping involves the analysis of geo-referenced disease incidence data and has many applications, for example within resource allocation, cluster alarm analysis, and ecological studies. There is a real need amongst public health workers for simpler and more efficient tools for the analysis of geo-referenced disease incidence data.

Recent progress in fast, parallel computing and in simulation-based inference has lead to the development of extremely powerful statistical tools. These can now be successfully applied to address the most pressing practical and ethical concerns arising from medical decision problems.

Offers guidance to forensic scientists with little dependence on mathematical ability. This book helps to assess DNA evidence and present that evidence in a courtroom setting.

Statistics and the Evaluation of Evidence for Forensic ScientistsThe leading resource in the statistical evaluation and interpretation of forensic evidenceThe third edition of Statistics and the Evaluation of Evidence for Forensic Scientists is fully updated to provide the latest research and developments in the use of statistical techniques to evaluate and interpret evidence. Courts are increasingly aware of the importance of proper evidence assessment when there is an element of uncertainty. Because of the increasing availability of data, the role of statistical and probabilistic reasoning is gaining a higher profile in criminal cases. That's why lawyers, forensic scientists, graduate students, and researchers will find this book an essential resource, one which explores how forensic evidence can be evaluated and interpreted statistically. It's written as an accessible source of information for all those with an interest in the evaluation and interpretation of forensic scientific evidence.* Discusses the entire chain of reasoning-from evidence pre-assessment to court presentation;* Includes material for the understanding of evidence interpretation for single and multiple trace evidence;* Provides real examples and data for improved understanding.Since the first edition of this book was published in 1995, this respected series has remained a leading resource in the statistical evaluation of forensic evidence. It shares knowledge from authors in the fields of statistics and forensic science who are international experts in the area of evidence evaluation and interpretation. This book helps people to deal with uncertainty related to scientific evidence and propositions. It introduces a method of reasoning that shows how to update beliefs coherently and to act rationally. In this edition, readers can find new information on the topics of elicitation, subjective probabilities, decision analysis, and cognitive bias, all discussed in a Bayesian framework.

READ ALL ABOUT IT! David Spiegelhalter has recently joined the ranks of Isaac Newton, Charles Darwin and Stephen Hawking by becoming a fellow of the Royal Society. Originating from the Medical Research Council's biostatistics unit, David has played a leading role in the Bristol heart surgery and Harold Shipman inquiries.

This text look at cross-over trials which are experiments in which subjects, whether patients or healthy volunteers, are each given a number of treatments with the object being to study the differences between these treatments. They are used extensively in clinical research.

Uncertain Judgments Eliciting Experts' Probabilities presents a range of tried and tested elicitation methods to enable statisticians to get make the most of expert opinion. An elicitation method forms a bridge between an expert's opinion and an expression of these points in a statistically useful form.

A state-of-the-art introduction to the powerful mathematical and statistical tools used in the field of finance The use of mathematical models and numerical techniques is a practice employed by a growing number of applied mathematicians working on applications in finance.

Dose-finding in practice is often done very poorly; conventional methods, which are in widespread use, can be unreliable and lead to inaccurate results. However, there have been many advances in recent years, with new sophisticated statistical techniques being developed. It is important that these new techniques are utilized correctly.

This text shows how stochastic geometry can be applied to real structural problems in materials science and technology. It pays particular attention to describing spatial sizes and shapes of grains and particles, developments in stochastic geometry, and relevant computer simulation techniques.

The statistical analysis of cost-effectiveness data is becoming increasingly important within health and medical research. Statistical Analysis of Cost-Effectiveness Data provides a practical book that synthesises the huge amount of research that has taken place in the area over the last two decades.

This book provides an introduction to both Bayesian methods and gene expression, accessible to people with backgrounds in either. The text is enhanced by the inclusion of numerous problems and solutions, designed with an emphasis on methodology and application.

A mixed model allows the incorporation of both fixed and random variables within a statistical analysis. This enables efficient inferences and more information to be gained from the data. The application of mixed models is an increasingly popular way of analysing medical data, particularly in the pharmaceutical industry.

The need to understand, interpret and analyse competing risk data is key to many areas of science, particularly medical research.

This book covers all the latest advances, as well as more established methods, in the application of statistical and optimisation methods within modern industry. These include applications from a range of industries that include micro-electronics, chemical, automotive, engineering, food, component assembly, household goods and plastics.

Statistical Monitoring of Complex Multivariate Processes summarizes recent advances in statistical-based process monitoring of complex multivariate process systems. The book includes a broad range of applications of multivariate statistical techniques into the area of mechanical, manufacturing, and power engineering.