statistical analysis of regional yield trials ammi analysis of factorial designs



Kerr Kathleen F. Design and Analysis of Experiments in the Health Sciences Kerr Kathleen F. Design and Analysis of Experiments in the Health Sciences Новинка

Kerr Kathleen F. Design and Analysis of Experiments in the Health Sciences

4977.25 руб.
An accessible and practical approach to the design and analysis of experiments in the health sciences Design and Analysis of Experiments in the Health Sciences provides a balanced presentation of design and analysis issues relating to data in the health sciences and emphasizes new research areas, the crucial topic of clinical trials, and state-of-the- art applications. Advancing the idea that design drives analysis and analysis reveals the design, the book clearly explains how to apply design and analysis principles in animal, human, and laboratory experiments while illustrating topics with applications and examples from randomized clinical trials and the modern topic of microarrays. The authors outline the following five types of designs that form the basis of most experimental structures: Completely randomized designs Randomized block designs Factorial designs Multilevel experiments Repeated measures designs A related website features a wealth of data sets that are used throughout the book, allowing readers to work hands-on with the material. In addition, an extensive bibliography outlines additional resources for further study of the presented topics. Requiring only a basic background in statistics, Design and Analysis of Experiments in the Health Sciences is an excellent book for introductory courses on experimental design and analysis at the graduate level. The book also serves as a valuable resource for researchers in medicine, dentistry, nursing, epidemiology, statistical genetics, and public health.
Chow Shein-Chung Design and Analysis of Clinical Trials. Concepts and Methodologies Chow Shein-Chung Design and Analysis of Clinical Trials. Concepts and Methodologies Новинка

Chow Shein-Chung Design and Analysis of Clinical Trials. Concepts and Methodologies

12261.12 руб.
Praise for the Second Edition: “…a grand feast for biostatisticians. It stands ready to satisfy the appetite of any pharmaceutical scientist with a respectable statistical appetite.” —Journal of Clinical Research Best Practices The Third Edition of Design and Analysis of Clinical Trials provides complete, comprehensive, and expanded coverage of recent health treatments and interventions. Featuring a unified presentation, the book provides a well-balanced summary of current regulatory requirements and recently developed statistical methods as well as an overview of the various designs and analyses that are utilized at different stages of clinical research and development. Additional features of this Third Edition include: • New chapters on biomarker development and target clinical trials, adaptive design, trials for evaluating diagnostic devices, statistical methods for translational medicine, and traditional Chinese medicine • A balanced overview of current and emerging clinical issues as well as newly developed statistical methodologies • Practical examples of clinical trials that demonstrate everyday applicability, with illustrations and examples to explain key concepts • New sections on bridging studies and global trials, QT studies, multinational trials, comparative effectiveness trials, and the analysis of QT/QTc prolongation • A complete and balanced presentation of clinical and scientific issues, statistical concepts, and methodologies for bridging clinical and statistical disciplines • An update of each chapter that reflects changes in regulatory requirements for the drug review and approval process and recent developments in statistical design and methodology for clinical research and development Design and Analysis of Clinical Trials, Third Edition continues to be an ideal clinical research reference for academic, pharmaceutical, medical, and regulatory scientists/researchers, statisticians, and graduate-level students.
Klaus Hinkelmann Design and Analysis of Experiments, Volume 3. Special Designs and Applications Klaus Hinkelmann Design and Analysis of Experiments, Volume 3. Special Designs and Applications Новинка

Klaus Hinkelmann Design and Analysis of Experiments, Volume 3. Special Designs and Applications

11111.64 руб.
Provides timely applications, modifications, and extensions of experimental designs for a variety of disciplines Design and Analysis of Experiments, Volume 3: Special Designs and Applications continues building upon the philosophical foundations of experimental design by providing important, modern applications of experimental design to the many fields that utilize them. The book also presents optimal and efficient designs for practice and covers key topics in current statistical research. Featuring contributions from leading researchers and academics, the book demonstrates how the presented concepts are used across various fields from genetics and medicinal and pharmaceutical research to manufacturing, engineering, and national security. Each chapter includes an introduction followed by the historical background as well as in-depth procedures that aid in the construction and analysis of the discussed designs. Topical coverage includes: Genetic cross experiments, microarray experiments, and variety trials Clinical trials, group-sequential designs, and adaptive designs Fractional factorial and search, choice, and optimal designs for generalized linear models Computer experiments with applications to homeland security Robust parameter designs and split-plot type response surface designs Analysis of directional data experiments Throughout the book, illustrative and numerical examples utilize SAS®, JMP®, and R software programs to demonstrate the discussed techniques. Related data sets and software applications are available on the book's related FTP site. Design and Analysis of Experiments, Volume 3 is an ideal textbook for graduate courses in experimental design and also serves as a practical, hands-on reference for statisticians and researchers across a wide array of subject areas, including biological sciences, engineering, medicine, and business.
N. Balakrishnan Methods and Applications of Statistics in Clinical Trials, Volume 1. Concepts, Principles, Trials, and Designs N. Balakrishnan Methods and Applications of Statistics in Clinical Trials, Volume 1. Concepts, Principles, Trials, and Designs Новинка

N. Balakrishnan Methods and Applications of Statistics in Clinical Trials, Volume 1. Concepts, Principles, Trials, and Designs

15517.06 руб.
A complete guide to the key statistical concepts essential for the design and construction of clinical trials As the newest major resource in the field of medical research, Methods and Applications of Statistics in Clinical Trials, Volume 1: Concepts, Principles, Trials, and Designs presents a timely and authoritative reviewof the central statistical concepts used to build clinical trials that obtain the best results. The referenceunveils modern approaches vital to understanding, creating, and evaluating data obtained throughoutthe various stages of clinical trial design and analysis. Accessible and comprehensive, the first volume in a two-part set includes newly-written articles as well as established literature from the Wiley Encyclopedia of Clinical Trials. Illustrating a variety of statistical concepts and principles such as longitudinal data, missing data, covariates, biased-coin randomization, repeated measurements, and simple randomization, the book also provides in-depth coverage of the various trial designs found within phase I-IV trials. Methods and Applications of Statistics in Clinical Trials, Volume 1: Concepts, Principles, Trials, and Designs also features: Detailed chapters on the type of trial designs, such as adaptive, crossover, group-randomized, multicenter, non-inferiority, non-randomized, open-labeled, preference, prevention, and superiority trials Over 100 contributions from leading academics, researchers, and practitioners An exploration of ongoing, cutting-edge clinical trials on early cancer and heart disease, mother-to-child human immunodeficiency virus transmission trials, and the AIDS Clinical Trials Group Methods and Applications of Statistics in Clinical Trials, Volume 1: Concepts, Principles, Trials, and Designs is an excellent reference for researchers, practitioners, and students in the fields of clinicaltrials, pharmaceutics, biostatistics, medical research design, biology, biomedicine, epidemiology,and public health.
Alfred Bartolucci Introduction to Statistical Analysis of Laboratory Data Alfred Bartolucci Introduction to Statistical Analysis of Laboratory Data Новинка

Alfred Bartolucci Introduction to Statistical Analysis of Laboratory Data

9372.7 руб.
Introduction to Statistical Analysis of Laboratory Data presents a detailed discussion of important statistical concepts and methods of data presentation and analysis Provides detailed discussions on statistical applications including a comprehensive package of statistical tools that are specific to the laboratory experiment process Introduces terminology used in many applications such as the interpretation of assay design and validation as well as “fit for purpose” procedures including real world examples Includes a rigorous review of statistical quality control procedures in laboratory methodologies and influences on capabilities Presents methodologies used in the areas such as method comparison procedures, limit and bias detection, outlier analysis and detecting sources of variation Analysis of robustness and ruggedness including multivariate influences on response are introduced to account for controllable/uncontrollable laboratory conditions
Nikolaos Limnios Statistical Models and Methods for Reliability and Survival Analysis Nikolaos Limnios Statistical Models and Methods for Reliability and Survival Analysis Новинка

Nikolaos Limnios Statistical Models and Methods for Reliability and Survival Analysis

14021.69 руб.
Statistical Models and Methods for Reliability and Survival Analysis brings together contributions by specialists in statistical theory as they discuss their applications providing up-to-date developments in methods used in survival analysis, statistical goodness of fit, stochastic processes for system reliability, amongst others. Many of these are related to the work of Professor M. Nikulin in statistics over the past 30 years. The authors gather together various contributions with a broad array of techniques and results, divided into three parts – Statistical Models and Methods, Statistical Models and Methods in Survival Analysis, and Reliability and Maintenance. The book is intended for researchers interested in statistical methodology and models useful in survival analysis, system reliability and statistical testing for censored and non-censored data.
Bradley Huitema The Analysis of Covariance and Alternatives. Statistical Methods for Experiments, Quasi-Experiments, and Single-Case Studies Bradley Huitema The Analysis of Covariance and Alternatives. Statistical Methods for Experiments, Quasi-Experiments, and Single-Case Studies Новинка

Bradley Huitema The Analysis of Covariance and Alternatives. Statistical Methods for Experiments, Quasi-Experiments, and Single-Case Studies

11111.64 руб.
A complete guide to cutting-edge techniques and best practices for applying covariance analysis methods The Second Edition of Analysis of Covariance and Alternatives sheds new light on its topic, offering in-depth discussions of underlying assumptions, comprehensive interpretations of results, and comparisons of distinct approaches. The book has been extensively revised and updated to feature an in-depth review of prerequisites and the latest developments in the field. The author begins with a discussion of essential topics relating to experimental design and analysis, including analysis of variance, multiple regression, effect size measures and newly developed methods of communicating statistical results. Subsequent chapters feature newly added methods for the analysis of experiments with ordered treatments, including two parametric and nonparametric monotone analyses as well as approaches based on the robust general linear model and reversed ordinal logistic regression. Four groundbreaking chapters on single-case designs introduce powerful new analyses for simple and complex single-case experiments. This Second Edition also features coverage of advanced methods including: Simple and multiple analysis of covariance using both the Fisher approach and the general linear model approach Methods to manage assumption departures, including heterogeneous slopes, nonlinear functions, dichotomous dependent variables, and covariates affected by treatments Power analysis and the application of covariance analysis to randomized-block designs, two-factor designs, pre- and post-test designs, and multiple dependent variable designs Measurement error correction and propensity score methods developed for quasi-experiments, observational studies, and uncontrolled clinical trials Thoroughly updated to reflect the growing nature of the field, Analysis of Covariance and Alternatives is a suitable book for behavioral and medical scineces courses on design of experiments and regression and the upper-undergraduate and graduate levels. It also serves as an authoritative reference work for researchers and academics in the fields of medicine, clinical trials, epidemiology, public health, sociology, and engineering.
Chihiro Hirotsu Advanced Analysis of Variance Chihiro Hirotsu Advanced Analysis of Variance Новинка

Chihiro Hirotsu Advanced Analysis of Variance

9372.7 руб.
Introducing a revolutionary new model for the statistical analysis of experimental data In this important book, internationally acclaimed statistician, Chihiro Hirotsu, goes beyond classical analysis of variance (ANOVA) model to offer a unified theory and advanced techniques for the statistical analysis of experimental data. Dr. Hirotsu introduces the groundbreaking concept of advanced analysis of variance (AANOVA) and explains how the AANOVA approach exceeds the limitations of ANOVA methods to allow for global reasoning utilizing special methods of simultaneous inference leading to individual conclusions. Focusing on normal, binomial, and categorical data, Dr. Hirotsu explores ANOVA theory and practice and reviews current developments in the field. He then introduces three new advanced approaches, namely: testing for equivalence and non-inferiority; simultaneous testing for directional (monotonic or restricted) alternatives and change-point hypotheses; and analyses emerging from categorical data. Using real-world examples, he shows how these three recognizable families of problems have important applications in most practical activities involving experimental data in an array of research areas, including bioequivalence, clinical trials, industrial experiments, pharmaco-statistics, and quality control, to name just a few. • Written in an expository style which will encourage readers to explore applications for AANOVA techniques in their own research • Focuses on dealing with real data, providing real-world examples drawn from the fields of statistical quality control, clinical trials, and drug testing • Describes advanced methods developed and refined by the author over the course of his long career as research engineer and statistician • Introduces advanced technologies for AANOVA data analysis that build upon the basic ANOVA principles and practices Introducing a breakthrough approach to statistical analysis which overcomes the limitations of the ANOVA model, Advanced Analysis of Variance is an indispensable resource for researchers and practitioners working in fields within which the statistical analysis of experimental data is a crucial research component. Chihiro Hirotsu is a Senior Researcher at the Collaborative Research Center, Meisei University, and Professor Emeritus at the University of Tokyo. He is a fellow of the American Statistical Association, an elected member of the International Statistical Institute, and he has been awarded the Japan Statistical Society Prize (2005) and the Ouchi Prize (2006). His work has been published in Biometrika, Biometrics, and Computational Statistics & Data Analysis, among other premier research journals.
Weikai Yan Crop Variety Trials. Data Management and Analysis Weikai Yan Crop Variety Trials. Data Management and Analysis Новинка

Weikai Yan Crop Variety Trials. Data Management and Analysis

11618.58 руб.
Variety trials are an essential step in crop breeding and production. These trials are a significant investment in time and resources and inform numerous decisions from cultivar development to end-use. Crop Variety Trials: Methods and Analysis is a practical volume that provides valuable theoretical foundations as well as a guide to step-by-step implementation of effective trial methods and analysis in determining the best varieties and cultivars. Crop Variety Trials is divided into two sections. The first section provides the reader with a sound theoretical framework of variety evaluation and trial analysis. Chapters provide insights into the theories of quantitative genetics and principles of analyzing data. The second section of the book gives the reader with a practical step-by-step guide to accurately analyzing crop variety trial data. Combined these sections provide the reader with fuller understanding of the nature of variety trials, their objectives, and user-friendly database and statistical tools that will enable them to produce accurate analysis of data.
Kristin Jarman H. The Art of Data Analysis. How to Answer Almost Any Question Using Basic Statistics Kristin Jarman H. The Art of Data Analysis. How to Answer Almost Any Question Using Basic Statistics Новинка

Kristin Jarman H. The Art of Data Analysis. How to Answer Almost Any Question Using Basic Statistics

4904.45 руб.
A friendly and accessible approach to applying statistics in the real world With an emphasis on critical thinking, The Art of Data Analysis: How to Answer Almost Any Question Using Basic Statistics presents fun and unique examples, guides readers through the entire data collection and analysis process, and introduces basic statistical concepts along the way. Leaving proofs and complicated mathematics behind, the author portrays the more engaging side of statistics and emphasizes its role as a problem-solving tool. In addition, light-hearted case studies illustrate the application of statistics to real data analyses, highlighting the strengths and weaknesses of commonly used techniques. Written for the growing academic and industrial population that uses statistics in everyday life, The Art of Data Analysis: How to Answer Almost Any Question Using Basic Statistics highlights important issues that often arise when collecting and sifting through data. Featured concepts include: • Descriptive statistics • Analysis of variance • Probability and sample distributions • Confidence intervals • Hypothesis tests • Regression • Statistical correlation • Data collection • Statistical analysis with graphs Fun and inviting from beginning to end, The Art of Data Analysis is an ideal book for students as well as managers and researchers in industry, medicine, or government who face statistical questions and are in need of an intuitive understanding of basic statistical reasoning.
Jae Lee K. Statistical Bioinformatics. For Biomedical and Life Science Researchers Jae Lee K. Statistical Bioinformatics. For Biomedical and Life Science Researchers Новинка

Jae Lee K. Statistical Bioinformatics. For Biomedical and Life Science Researchers

9805.06 руб.
This book provides an essential understanding of statistical concepts necessary for the analysis of genomic and proteomic data using computational techniques. The author presents both basic and advanced topics, focusing on those that are relevant to the computational analysis of large data sets in biology. Chapters begin with a description of a statistical concept and a current example from biomedical research, followed by more detailed presentation, discussion of limitations, and problems. The book starts with an introduction to probability and statistics for genome-wide data, and moves into topics such as clustering, classification, multi-dimensional visualization, experimental design, statistical resampling, and statistical network analysis. Clearly explains the use of bioinformatics tools in life sciences research without requiring an advanced background in math/statistics Enables biomedical and life sciences researchers to successfully evaluate the validity of their results and make inferences Enables statistical and quantitative researchers to rapidly learn novel statistical concepts and techniques appropriate for large biological data analysis Carefully revisits frequently used statistical approaches and highlights their limitations in large biological data analysis Offers programming examples and datasets Includes chapter problem sets, a glossary, a list of statistical notations, and appendices with references to background mathematical and technical material Features supplementary materials, including datasets, links, and a statistical package available online Statistical Bioinformatics is an ideal textbook for students in medicine, life sciences, and bioengineering, aimed at researchers who utilize computational tools for the analysis of genomic, proteomic, and many other emerging high-throughput molecular data. It may also serve as a rapid introduction to the bioinformatics science for statistical and computational students and audiences who have not experienced such analysis tasks before.
Elisa Lee T. Statistical Methods for Survival Data Analysis Elisa Lee T. Statistical Methods for Survival Data Analysis Новинка

Elisa Lee T. Statistical Methods for Survival Data Analysis

10047.81 руб.
Praise for the Third Edition “. . . an easy-to read introduction to survival analysis which covers the major concepts and techniques of the subject.” —Statistics in Medical Research Updated and expanded to reflect the latest developments, Statistical Methods for Survival Data Analysis, Fourth Edition continues to deliver a comprehensive introduction to the most commonly-used methods for analyzing survival data. Authored by a uniquely well-qualified author team, the Fourth Edition is a critically acclaimed guide to statistical methods with applications in clinical trials, epidemiology, areas of business, and the social sciences. The book features many real-world examples to illustrate applications within these various fields, although special consideration is given to the study of survival data in biomedical sciences. Emphasizing the latest research and providing the most up-to-date information regarding software applications in the field, Statistical Methods for Survival Data Analysis, Fourth Edition also includes: Marginal and random effect models for analyzing correlated censored or uncensored data Multiple types of two-sample and K-sample comparison analysis Updated treatment of parametric methods for regression model fitting with a new focus on accelerated failure time models Expanded coverage of the Cox proportional hazards model Exercises at the end of each chapter to deepen knowledge of the presented material Statistical Methods for Survival Data Analysis is an ideal text for upper-undergraduate and graduate-level courses on survival data analysis. The book is also an excellent resource for biomedical investigators, statisticians, and epidemiologists, as well as researchers in every field in which the analysis of survival data plays a role.
Simon Dadson James Statistical Analysis of Geographical Data. An Introduction Simon Dadson James Statistical Analysis of Geographical Data. An Introduction Новинка

Simon Dadson James Statistical Analysis of Geographical Data. An Introduction

2995.71 руб.
Statistics Analysis of Geographical Data: An Introduction provides a comprehensive and accessible introduction to the theory and practice of statistical analysis in geography. It covers a wide range of topics including graphical and numerical description of datasets, probability, calculation of confidence intervals, hypothesis testing, collection and analysis of data using analysis of variance and linear regression. Taking a clear and logical approach, this book examines real problems with real data from the geographical literature in order to illustrate the important role that statistics play in geographical investigations. Presented in a clear and accessible manner the book includes recent, relevant examples, designed to enhance the reader’s understanding.
Rassoul Noorossana Statistical Analysis of Profile Monitoring Rassoul Noorossana Statistical Analysis of Profile Monitoring Новинка

Rassoul Noorossana Statistical Analysis of Profile Monitoring

9897.71 руб.
A one-of-a-kind presentation of the major achievements in statistical profile monitoring methods Statistical profile monitoring is an area of statistical quality control that is growing in significance for researchers and practitioners, specifically because of its range of applicability across various service and manufacturing settings. Comprised of contributions from renowned academicians and practitioners in the field, Statistical Analysis of Profile Monitoring presents the latest state-of-the-art research on the use of control charts to monitor process and product quality profiles. The book presents comprehensive coverage of profile monitoring definitions, techniques, models, and application examples, particularly in various areas of engineering and statistics. The book begins with an introduction to the concept of profile monitoring and its applications in practice. Subsequent chapters explore the fundamental concepts, methods, and issues related to statistical profile monitoring, with topics of coverage including: Simple and multiple linear profiles Binary response profiles Parametric and nonparametric nonlinear profiles Multivariate linear profiles monitoring Statistical process control for geometric specifications Correlation and autocorrelation in profiles Nonparametric profile monitoring Throughout the book, more than two dozen real-world case studies highlight the discussed topics along with innovative examples and applications of profile monitoring. Statistical Analysis of Profile Monitoring is an excellent book for courses on statistical quality control at the graduate level. It also serves as a valuable reference for quality engineers, researchers and anyone who works in monitoring and improving statistical processes.
David Machin Quality of Life. The Assessment, Analysis and Reporting of Patient-reported Outcomes David Machin Quality of Life. The Assessment, Analysis and Reporting of Patient-reported Outcomes Новинка

David Machin Quality of Life. The Assessment, Analysis and Reporting of Patient-reported Outcomes

7683.12 руб.
The assessment of patient reported outcomes and health-related quality of life continue to be rapidly evolving areas of research and this new edition reflects the development within the field from an emerging subject to one that is an essential part of the assessment of clinical trials and other clinical studies. The analysis and interpretation of quality-of-life assessments relies on a variety of psychometric and statistical methods which are explained in this book in a non-technical way. The result is a practical guide that covers a wide range of methods and emphasizes the use of simple techniques that are illustrated with numerous examples, with extensive chapters covering qualitative and quantitative methods and the impact of guidelines. The material in this new third edition reflects current teaching methods and content widened to address continuing developments in item response theory, computer adaptive testing, analyses with missing data, analysis of ordinal data, systematic reviews and meta-analysis. This book is aimed at everyone involved in quality-of-life research and is applicable to medical and non-medical, statistical and non-statistical readers. It is of particular relevance for clinical and biomedical researchers within both the pharmaceutical industry and clinical practice.
A. Gould Lawrence Statistical Methods for Evaluating Safety in Medical Product Development A. Gould Lawrence Statistical Methods for Evaluating Safety in Medical Product Development Новинка

A. Gould Lawrence Statistical Methods for Evaluating Safety in Medical Product Development

7889.26 руб.
This book gives professionals in clinical research valuable information on the challenging issues of the design, execution, and management of clinical trials, and how to resolve these issues effectively. It also provides understanding and practical guidance on the application of contemporary statistical methods to contemporary issues in safety evaluation during medical product development. Each chapter provides sufficient detail to the reader to undertake the design and analysis of experiments at various stages of product development, including comprehensive references to the relevant literature. Provides a guide to statistical methods and application in medical product development Assists readers in undertaking design and analysis of experiments at various stages of product development Features case studies throughout the book, as well as, SAS and R code
Richard Kay Statistical Thinking for Non-Statisticians in Drug Regulation Richard Kay Statistical Thinking for Non-Statisticians in Drug Regulation Новинка

Richard Kay Statistical Thinking for Non-Statisticians in Drug Regulation

7889.26 руб.
Statistical Thinking for Non-Statisticians in Drug Regulation, Second Edition, is a need-to-know guide to understanding statistical methodology, statistical data and results within drug development and clinical trials. It provides non-statisticians working in the pharmaceutical and medical device industries with an accessible introduction to the knowledge they need when working with statistical information and communicating with statisticians. It covers the statistical aspects of design, conduct, analysis and presentation of data from clinical trials in drug regulation and improves the ability to read, understand and critically appraise statistical methodology in papers and reports. As such, it is directly concerned with the day-to-day practice and the regulatory requirements of drug development and clinical trials. Fully conversant with current regulatory requirements, this second edition includes five new chapters covering Bayesian statistics, adaptive designs, observational studies, methods for safety analysis and monitoring and statistics for diagnosis. Authored by a respected lecturer and consultant to the pharmaceutical industry, Statistical Thinking for Non-Statisticians in Drug Regulation is an ideal guide for physicians, clinical research scientists, managers and associates, data managers, medical writers, regulatory personnel and for all non-statisticians working and learning within the pharmaceutical industry.
Henrik Holbech Statistical Analysis of Ecotoxicity Studies Henrik Holbech Statistical Analysis of Ecotoxicity Studies Новинка

Henrik Holbech Statistical Analysis of Ecotoxicity Studies

8940.4 руб.
A guide to the issues relevant to the design, analysis, and interpretation of toxicity studies that examine chemicals for use in the environment Statistical Analysis of Ecotoxicity Studies offers a guide to the design, analysis, and interpretation of a range of experiments that are used to assess the toxicity of chemicals. While the book highlights ecotoxicity studies, the methods presented are applicable to the broad range of toxicity studies. The text contains myriad datasets (from laboratory and field research) that clearly illustrate the book’s topics. The datasets reveal the techniques, pitfalls, and precautions derived from these studies. The text includes information on recently developed methods for the analysis of severity scores and other ordered responses, as well as extensive power studies of competing tests and computer simulation studies of regression models that offer an understanding of the sensitivity (or lack thereof) of various methods and the quality of parameter estimates from regression models. The authors also discuss the regulatory process indicating how test guidelines are developed and review the statistical methodology in current or pending OECD and USEPA ecotoxicity guidelines. This important guide: • Offers the information needed for the design and analysis to a wide array of ecotoxicity experiments and to the development of international test guidelines used to assess the toxicity of chemicals • Contains a thorough examination of the statistical issues that arise in toxicity studies, especially ecotoxicity • Includes an introduction to toxicity experiments and statistical analysis basics • Includes programs in R and excel • Covers the analysis of continuous and Quantal data, analysis of data as well as Regulatory Issues • Presents additional topics (Mesocosm and Microplate experiments, mixtures of chemicals, benchmark dose models, and limit tests) as well as software Written for directors, scientists, regulators, and technicians, Statistical Analysis of Ecotoxicity Studies provides a sound understanding of the technical and practical issues in designing, analyzing, and interpreting toxicity studies to support or challenge chemicals for use in the environment.
Alex Karagrigoriou Applied Reliability Engineering and Risk Analysis. Probabilistic Models and Statistical Inference Alex Karagrigoriou Applied Reliability Engineering and Risk Analysis. Probabilistic Models and Statistical Inference Новинка

Alex Karagrigoriou Applied Reliability Engineering and Risk Analysis. Probabilistic Models and Statistical Inference

13646.79 руб.
This complete resource on the theory and applications of reliability engineering, probabilistic models and risk analysis consolidates all the latest research, presenting the most up-to-date developments in this field. With comprehensive coverage of the theoretical and practical issues of both classic and modern topics, it also provides a unique commemoration to the centennial of the birth of Boris Gnedenko, one of the most prominent reliability scientists of the twentieth century. Key features include: expert treatment of probabilistic models and statistical inference from leading scientists, researchers and practitioners in their respective reliability fields detailed coverage of multi-state system reliability, maintenance models, statistical inference in reliability, systemability, physics of failures and reliability demonstration many examples and engineering case studies to illustrate the theoretical results and their practical applications in industry Applied Reliability Engineering and Risk Analysis is one of the first works to treat the important areas of degradation analysis, multi-state system reliability, networks and large-scale systems in one comprehensive volume. It is an essential reference for engineers and scientists involved in reliability analysis, applied probability and statistics, reliability engineering and maintenance, logistics, and quality control. It is also a useful resource for graduate students specialising in reliability analysis and applied probability and statistics. Dedicated to the Centennial of the birth of Boris Gnedenko, renowned Russian mathematician and reliability theorist
A. Guarino J. Performing Data Analysis Using IBM SPSS A. Guarino J. Performing Data Analysis Using IBM SPSS Новинка

A. Guarino J. Performing Data Analysis Using IBM SPSS

7947.76 руб.
Features easy-to-follow insight and clear guidelines to perform data analysis using IBM SPSS® Performing Data Analysis Using IBM SPSS® uniquely addresses the presented statistical procedures with an example problem, detailed analysis, and the related data sets. Data entry procedures, variable naming, and step-by-step instructions for all analyses are provided in addition to IBM SPSS point-and-click methods, including details on how to view and manipulate output. Designed as a user’s guide for students and other interested readers to perform statistical data analysis with IBM SPSS, this book addresses the needs, level of sophistication, and interest in introductory statistical methodology on the part of readers in social and behavioral science, business, health-related, and education programs. Each chapter of Performing Data Analysis Using IBM SPSS covers a particular statistical procedure and offers the following: an example problem or analysis goal, together with a data set; IBM SPSS analysis with step-by-step analysis setup and accompanying screen shots; and IBM SPSS output with screen shots and narrative on how to read or interpret the results of the analysis. The book provides in-depth chapter coverage of: IBM SPSS statistical output Descriptive statistics procedures Score distribution assumption evaluations Bivariate correlation Regressing (predicting) quantitative and categorical variables Survival analysis t Test ANOVA and ANCOVA Multivariate group differences Multidimensional scaling Cluster analysis Nonparametric procedures for frequency data Performing Data Analysis Using IBM SPSS is an excellent text for upper-undergraduate and graduate-level students in courses on social, behavioral, and health sciences as well as secondary education, research design, and statistics. Also an excellent reference, the book is ideal for professionals and researchers in the social, behavioral, and health sciences; applied statisticians; and practitioners working in industry.
Wolfgang Wiedermann Statistics and Causality. Methods for Applied Empirical Research Wolfgang Wiedermann Statistics and Causality. Methods for Applied Empirical Research Новинка

Wolfgang Wiedermann Statistics and Causality. Methods for Applied Empirical Research

8622.88 руб.
A one-of-a-kind guide to identifying and dealing with modern statistical developments in causality Written by a group of well-known experts, Statistics and Causality: Methods for Applied Empirical Research focuses on the most up-to-date developments in statistical methods in respect to causality. Illustrating the properties of statistical methods to theories of causality, the book features a summary of the latest developments in methods for statistical analysis of causality hypotheses. The book is divided into five accessible and independent parts. The first part introduces the foundations of causal structures and discusses issues associated with standard mechanistic and difference-making theories of causality. The second part features novel generalizations of methods designed to make statements concerning the direction of effects. The third part illustrates advances in Granger-causality testing and related issues. The fourth part focuses on counterfactual approaches and propensity score analysis. Finally, the fifth part presents designs for causal inference with an overview of the research designs commonly used in epidemiology. Statistics and Causality: Methods for Applied Empirical Research also includes: New statistical methodologies and approaches to causal analysis in the context of the continuing development of philosophical theories End-of-chapter bibliographies that provide references for further discussions and additional research topics Discussions on the use and applicability of software when appropriate Statistics and Causality: Methods for Applied Empirical Research is an ideal reference for practicing statisticians, applied mathematicians, psychologists, sociologists, logicians, medical professionals, epidemiologists, and educators who want to learn more about new methodologies in causal analysis. The book is also an excellent textbook for graduate-level courses in causality and qualitative logic.
Salah Khalfallah Structural Analysis 1. Statically Determinate Structures Salah Khalfallah Structural Analysis 1. Statically Determinate Structures Новинка

Salah Khalfallah Structural Analysis 1. Statically Determinate Structures

10536.9 руб.
Using a general approach, this book supports the student to enable mastery of the methods of analysis of isostatic and hyperstatic structures. To show the performance of the methods of analysis of the hyperstatic structures, selected beams, gantries and reticular structures are selected and subjected to a comparative study by the different methods of analysis of the hyperstatic structures.
Ю. В. Лысенко Analysis technique and risk assessment of insolvency of machine-building enterprise Ю. В. Лысенко Analysis technique and risk assessment of insolvency of machine-building enterprise Новинка

Ю. В. Лысенко Analysis technique and risk assessment of insolvency of machine-building enterprise

550 руб.
The monograph is devoted to a problem of production and sale of the concentrating and mountain equipment. The economic evaluation of production and sale is opened in the following sequence. The economic essence of the concept «insolvency» of the entity is stated. The reasons of risk of insolvency, its role in diagnostic approaches to solvency analysis of the entity, are called and analysed possibilities of a risk assessment of insolvency of the entity. By means of assessment of a condition the model of the analysis and a risk assessment of insolvency of the entity, an algorithm of its application in the analysis of machine-building enterprise is developed. Assessment of a condition of production and sale is carried out based on huge statistical material on influence of structure and structure of current assets on solvency of machinebuilding enterprise, liquidity of balance and assessment of liquidity and efficiency of cash flows for strengthening and optimization of activities. With use of integration of methods approbation of an analysis technique and a risk assessment of insolvency of machine-building enterprise is carried out and the possibilities of its optimization are considered. In an analysis result, assessment and developed offers the management concept is formulated by liquidity of machine-building enterprise and decrease in risk of insolvency, the principles of its forming and the mechanism of implementation are shown.
Nancy Obuchowski A. Handbook for Clinical Trials of Imaging and Image-Guided Interventions Nancy Obuchowski A. Handbook for Clinical Trials of Imaging and Image-Guided Interventions Новинка

Nancy Obuchowski A. Handbook for Clinical Trials of Imaging and Image-Guided Interventions

7494.6 руб.
Handbook for Clinical Trials of Imaging and Image-Guided Interventions is the first single-source, multi-disciplinary reference, based on the didactic sessions presented at the annual ‘Clinical Trials Methodology Workshop’ for radiologists, radiation oncologists and imaging scientists (sponsored by the Radiological Society of North America (RSNA)). It focuses on educating radiologists, radiation oncologists and those involved in imaging research with how to design and conduct clinical trials to evaluate imaging technology and imaging biomarkers. The internationally renowned contributors take a broad approach, starting with principles of technology assessment, and then move into specific topics covering the clinical trials of therapy and clinical research in imaging guided interventions including radiotherapy. They discuss the use of imaging as a predictor of therapeutic response, screening trial design, and the practicalities of how to run an efficient clinical trial and good working practices. Later chapters provide a comprehensive array of quantitative methods including: an introduction to statistical considerations in study design, biostatistical analysis methods and their role in clinical imaging research, methods for quantitative imaging biomarker studies, and an introduction to cost effectiveness analysis. Handbook for Clinical Trials of Imaging and Image-Guided Interventions will educate and prepare radiologists at all levels and in all capacities in planning and conducting clinical imaging trials.
Antonio Napolitano Generalizations of Cyclostationary Signal Processing. Spectral Analysis and Applications Antonio Napolitano Generalizations of Cyclostationary Signal Processing. Spectral Analysis and Applications Новинка

Antonio Napolitano Generalizations of Cyclostationary Signal Processing. Spectral Analysis and Applications

11494.8 руб.
The relative motion between the transmitter and the receiver modifies the nonstationarity properties of the transmitted signal. In particular, the almost-cyclostationarity property exhibited by almost all modulated signals adopted in communications, radar, sonar, and telemetry can be transformed into more general kinds of nonstationarity. A proper statistical characterization of the received signal allows for the design of signal processing algorithms for detection, estimation, and classification that significantly outperform algorithms based on classical descriptions of signals.Generalizations of Cyclostationary Signal Processing addresses these issues and includes the following key features: Presents the underlying theoretical framework, accompanied by details of their practical application, for the mathematical models of generalized almost-cyclostationary processes and spectrally correlated processes; two classes of signals finding growing importance in areas such as mobile communications, radar and sonar. Explains second- and higher-order characterization of nonstationary stochastic processes in time and frequency domains. Discusses continuous- and discrete-time estimators of statistical functions of generalized almost-cyclostationary processes and spectrally correlated processes. Provides analysis of mean-square consistency and asymptotic Normality of statistical function estimators. Offers extensive analysis of Doppler channels owing to the relative motion between transmitter and receiver and/or surrounding scatterers. Performs signal analysis using both the classical stochastic-process approach and the functional approach, where statistical functions are built starting from a single function of time.
Mackenzie Lynette Occupation Analysis in Practice Mackenzie Lynette Occupation Analysis in Practice Новинка

Mackenzie Lynette Occupation Analysis in Practice

4444.02 руб.
Occupation Analysis in Practice is the essential book for all future and current occupational therapists. It offers a practical approach to the analysis of occupations in real world practice. The book frames occupation as the key component for analysis and builds upon previous work limited to analysis at the activity level. It examines the interests, goals, abilities and contexts of individuals, groups, institutions and communities, along with the demands of the occupation. It presents examples of occupation analysis in different practice context including working with children, health promotion, indigenous health, medico-legal practice; mental health and occupational rehabilitation. The book has four sections. Section 1 introduces theoretical perspectives of the concept of occupation analysis and how such analysis relates to particular models of Occupational Therapy practice and the generic World Health Organisation International Classification of Functioning, Disability and Health. Section 2 discusses analysis of particular components of occupation that support practice. These include culture, spirituality, home and community environments as well as self-care and leisure. Section 3 applies analysis of occupations to particular specialties encountered in practice. Section 4 considers the application of Occupation Analysis within professional reasoning and goal setting. FEATURES International team of contributors Examples of occupation analysis proforma Application to a wide range of practice areas. Glossary of key terms Incudes the International Classification of Functioning, Disability and Health.
Matthias Dehmer Applied Statistics for Network Biology. Methods in Systems Biology Matthias Dehmer Applied Statistics for Network Biology. Methods in Systems Biology Новинка

Matthias Dehmer Applied Statistics for Network Biology. Methods in Systems Biology

14093.55 руб.
The book introduces to the reader a number of cutting edge statistical methods which can e used for the analysis of genomic, proteomic and metabolomic data sets. In particular in the field of systems biology, researchers are trying to analyze as many data as possible in a given biological system (such as a cell or an organ). The appropriate statistical evaluation of these large scale data is critical for the correct interpretation and different experimental approaches require different approaches for the statistical analysis of these data. This book is written by biostatisticians and mathematicians but aimed as a valuable guide for the experimental researcher as well computational biologists who often lack an appropriate background in statistical analysis.
Ilya Narsky Statistical Analysis Techniques in Particle Physics. Fits, Density Estimation and Supervised Learning Ilya Narsky Statistical Analysis Techniques in Particle Physics. Fits, Density Estimation and Supervised Learning Новинка

Ilya Narsky Statistical Analysis Techniques in Particle Physics. Fits, Density Estimation and Supervised Learning

8922.38 руб.
Modern analysis of HEP data needs advanced statistical tools to separate signal from background. This is the first book which focuses on machine learning techniques. It will be of interest to almost every high energy physicist, and, due to its coverage, suitable for students.
Guttman Irwin Statistics and Probability with Applications for Engineers and Scientists Guttman Irwin Statistics and Probability with Applications for Engineers and Scientists Новинка

Guttman Irwin Statistics and Probability with Applications for Engineers and Scientists

11111.64 руб.
Introducing the tools of statistics and probability from the ground up An understanding of statistical tools is essential for engineers and scientists who often need to deal with data analysis over the course of their work. Statistics and Probability with Applications for Engineers and Scientists walks readers through a wide range of popular statistical techniques, explaining step-by-step how to generate, analyze, and interpret data for diverse applications in engineering and the natural sciences. Unique among books of this kind, Statistics and Probability with Applications for Engineers and Scientists covers descriptive statistics first, then goes on to discuss the fundamentals of probability theory. Along with case studies, examples, and real-world data sets, the book incorporates clear instructions on how to use the statistical packages Minitab® and Microsoft® Office Excel® to analyze various data sets. The book also features: • Detailed discussions on sampling distributions, statistical estimation of population parameters, hypothesis testing, reliability theory, statistical quality control including Phase I and Phase II control charts, and process capability indices • A clear presentation of nonparametric methods and simple and multiple linear regression methods, as well as a brief discussion on logistic regression method • Comprehensive guidance on the design of experiments, including randomized block designs, one- and two-way layout designs, Latin square designs, random effects and mixed effects models, factorial and fractional factorial designs, and response surface methodology • A companion website containing data sets for Minitab and Microsoft Office Excel, as well as JMP ® routines and results Assuming no background in probability and statistics, Statistics and Probability with Applications for Engineers and Scientists features a unique, yet tried-and-true, approach that is ideal for all undergraduate students as well as statistical practitioners who analyze and illustrate real-world data in engineering and the natural sciences.
G. Antille Descriptive Analysis of Matrix-Valued Time-Series G. Antille Descriptive Analysis of Matrix-Valued Time-Series Новинка

G. Antille Descriptive Analysis of Matrix-Valued Time-Series

79.9 руб.
In this article we present a technique of data analysis applied to three-dimensional tables as, for instance, matrix-valued time-series. The main goal of the method is to describe the evolution of the statistical units with respect to time in a space summarizing the set of matrices. Moreover, our technique points out similar statistical units provided by a classification of their trajectories.
Suresh Ramaiah A Course in Statistics with R Suresh Ramaiah A Course in Statistics with R Новинка

Suresh Ramaiah A Course in Statistics with R

7170.91 руб.
Integrates the theory and applications of statistics using R A Course in Statistics with R has been written to bridge the gap between theory and applications and explain how mathematical expressions are converted into R programs. The book has been primarily designed as a useful companion for a Masters student during each semester of the course, but will also help applied statisticians in revisiting the underpinnings of the subject. With this dual goal in mind, the book begins with R basics and quickly covers visualization and exploratory analysis. Probability and statistical inference, inclusive of classical, nonparametric, and Bayesian schools, is developed with definitions, motivations, mathematical expression and R programs in a way which will help the reader to understand the mathematical development as well as R implementation. Linear regression models, experimental designs, multivariate analysis, and categorical data analysis are treated in a way which makes effective use of visualization techniques and the related statistical techniques underlying them through practical applications, and hence helps the reader to achieve a clear understanding of the associated statistical models. Key features: Integrates R basics with statistical concepts Provides graphical presentations inclusive of mathematical expressions Aids understanding of limit theorems of probability with and without the simulation approach Presents detailed algorithmic development of statistical models from scratch Includes practical applications with over 50 data sets
T. Datta K. Seismic Analysis of Structures T. Datta K. Seismic Analysis of Structures Новинка

T. Datta K. Seismic Analysis of Structures

13027.44 руб.
While numerous books have been written on earthquakes, earthquake resistance design, and seismic analysis and design of structures, none have been tailored for advanced students and practitioners, and those who would like to have most of the important aspects of seismic analysis in one place. With this book, readers will gain proficiencies in the following: fundamentals of seismology that all structural engineers must know; various forms of seismic inputs; different types of seismic analysis like, time and frequency domain analyses, spectral analysis of structures for random ground motion, response spectrum method of analysis; equivalent lateral load analysis as given in earthquake codes; inelastic response analysis and the concept of ductility; ground response analysis and seismic soil structure interaction; seismic reliability analysis of structures; and control of seismic response of structures. Provides comprehensive coverage, from seismology to seismic control Contains useful empirical equations often required in the seismic analysis of structures Outlines explicit steps for seismic analysis of MDOF systems with multi support excitations Works through solved problems to illustrate different concepts Makes use of MATLAB, SAP2000 and ABAQUAS in solving example problems of the book Provides numerous exercise problems to aid understanding of the subject As one of the first books to present such a comprehensive treatment of the topic, Seismic Analysis of Structures is ideal for postgraduates and researchers in Earthquake Engineering, Structural Dynamics, and Geotechnical Earthquake Engineering. Developed for classroom use, the book can also be used for advanced undergraduate students planning for a career or further study in the subject area. The book will also better equip structural engineering consultants and practicing engineers in the use of standard software for seismic analysis of buildings, bridges, dams, and towers. Lecture materials for instructors available at www.wiley.com/go/dattaseismic
Salah Khalfallah Structural Analysis 2. Statically Indeterminate Structures Salah Khalfallah Structural Analysis 2. Statically Indeterminate Structures Новинка

Salah Khalfallah Structural Analysis 2. Statically Indeterminate Structures

15173.14 руб.
This book enables the student to master the methods of analysis of isostatic and hyperstatic structures. To show the performance of the methods of analysis of the hyperstatic structures, some beams, gantries and reticular structures are selected and subjected to a comparative study by the different methods of analysis of the hyperstatic structures. This procedure provides an insight into the methods of analysis of the structures.
Chap Le T. Introductory Biostatistics Chap Le T. Introductory Biostatistics Новинка

Chap Le T. Introductory Biostatistics

10123.22 руб.
Maintaining the same accessible and hands-on presentation, Introductory Biostatistics, Second Edition continues to provide an organized introduction to basic statistical concepts commonly applied in research across the health sciences. With plenty of real-world examples, the new edition provides a practical, modern approach to the statistical topics found in the biomedical and public health fields. Beginning with an overview of descriptive statistics in the health sciences, the book delivers topical coverage of probability models, parameter estimation, and hypothesis testing. Subsequently, the book focuses on more advanced topics with coverage of regression analysis, logistic regression, methods for count data, analysis of survival data, and designs for clinical trials. This extensive update of Introductory Biostatistics, Second Edition includes: • A new chapter on the use of higher order Analysis of Variance (ANOVA) in factorial and block designs • A new chapter on testing and inference methods for repeatedly measured outcomes including continuous, binary, and count outcomes • R incorporated throughout along with SAS®, allowing readers to replicate results from presented examples with either software • Multiple additional exercises, with partial solutions available to aid comprehension of crucial concepts • Notes on Computations sections to provide further guidance on the use of software • A related website that hosts the large data sets presented throughout the book Introductory Biostatistics, Second Edition is an excellent textbook for upper-undergraduate and graduate students in introductory biostatistics courses. The book is also an ideal reference for applied statisticians working in the fields of public health, nursing, dentistry, and medicine.
Dieter Rasch Statistics in Psychology Using R and SPSS Dieter Rasch Statistics in Psychology Using R and SPSS Новинка

Dieter Rasch Statistics in Psychology Using R and SPSS

7197.95 руб.
Statistics in Psychology covers all statistical methods needed in education and research in psychology. This book looks at research questions when planning data sampling, that is to design the intended study and to calculate the sample sizes in advance. In other words, no analysis applies if the minimum size is not determined in order to fulfil certain precision requirements. The book looks at the process of empirical research into the following seven stages: Formulation of the problem Stipulation of the precision requirements Selecting the statistical model for the planning and analysis The (optimal) design of the experiment or survey Performing the experiment or the survey Statistical analysis of the observed results Interpretation of the results.
Stephen W. Freiman The Fracture of Brittle Materials. Testing and Analysis Stephen W. Freiman The Fracture of Brittle Materials. Testing and Analysis Новинка

Stephen W. Freiman The Fracture of Brittle Materials. Testing and Analysis

9579 руб.
Provides a modern, practical approach to the understanding and measurement procedures relevant to the fracture of brittle materials This book examines the testing and analysis of the fracture of brittle materials. Expanding on the measurement and analysis methodology contained in the first edition, it covers the relevant measurements (toughness and strength), material types, fracture mechanics, measurement techniques, reliability and lifetime predictions, microstructural considerations, and material/test selection processes appropriate for the analysis of the fracture behavior of brittle materials. The Fracture of Brittle Materials: Testing and Analysis, Second Edition summarizes the concepts behind the selection of a test procedure for fracture toughness and strength, and goes into detail on how the statistics of fracture can be used to assure reliability. It explains the importance of the role of microstructure in these determinations and emphasizes the use of fractographic analysis as an important tool in understanding why a part failed. The new edition includes a significant quantity of material related to the fracture of biomaterials, and features two new chapters—one on thermal shock, the other on the modeling of the fracture process. It also expands on a discussion of how to treat the statistics of fracture strength data to ensure reliability. Provides practical analysis of fracture toughness and strength Introduces the engineering and materials student to the basic concepts necessary for analyzing brittle fracture Contains new statistical analysis procedures to allow for the prediction of the safe design of brittle components Contains real-world examples to assist the reader in applying the concepts to their own research, material development, and quality-control needs The Fracture of Brittle Materials: Testing and Analysis, Second Edition is an important resource for all students, technicians, engineers, scientists, and researchers involved in the study, analysis, creation, or testing of ceramics.
Hadi Ali S. Regression Analysis by Example Hadi Ali S. Regression Analysis by Example Новинка

Hadi Ali S. Regression Analysis by Example

10192.06 руб.
Praise for the Fourth Edition: «This book is . . . an excellent source of examples for regression analysis. It has been and still is readily readable and understandable.» —Journal of the American Statistical Association Regression analysis is a conceptually simple method for investigating relationships among variables. Carrying out a successful application of regression analysis, however, requires a balance of theoretical results, empirical rules, and subjective judgment. Regression Analysis by Example, Fifth Edition has been expanded and thoroughly updated to reflect recent advances in the field. The emphasis continues to be on exploratory data analysis rather than statistical theory. The book offers in-depth treatment of regression diagnostics, transformation, multicollinearity, logistic regression, and robust regression. The book now includes a new chapter on the detection and correction of multicollinearity, while also showcasing the use of the discussed methods on newly added data sets from the fields of engineering, medicine, and business. The Fifth Edition also explores additional topics, including: Surrogate ridge regression Fitting nonlinear models Errors in variables ANOVA for designed experiments Methods of regression analysis are clearly demonstrated, and examples containing the types of irregularities commonly encountered in the real world are provided. Each example isolates one or two techniques and features detailed discussions, the required assumptions, and the evaluated success of each technique. Additionally, methods described throughout the book can be carried out with most of the currently available statistical software packages, such as the software package R. Regression Analysis by Example, Fifth Edition is suitable for anyone with an understanding of elementary statistics.
Kerrie Mengersen L. Case Studies in Bayesian Statistical Modelling and Analysis Kerrie Mengersen L. Case Studies in Bayesian Statistical Modelling and Analysis Новинка

Kerrie Mengersen L. Case Studies in Bayesian Statistical Modelling and Analysis

7873.78 руб.
Provides an accessible foundation to Bayesian analysis using real world models This book aims to present an introduction to Bayesian modelling and computation, by considering real case studies drawn from diverse fields spanning ecology, health, genetics and finance. Each chapter comprises a description of the problem, the corresponding model, the computational method, results and inferences as well as the issues that arise in the implementation of these approaches. Case Studies in Bayesian Statistical Modelling and Analysis: Illustrates how to do Bayesian analysis in a clear and concise manner using real-world problems. Each chapter focuses on a real-world problem and describes the way in which the problem may be analysed using Bayesian methods. Features approaches that can be used in a wide area of application, such as, health, the environment, genetics, information science, medicine, biology, industry and remote sensing. Case Studies in Bayesian Statistical Modelling and Analysis is aimed at statisticians, researchers and practitioners who have some expertise in statistical modelling and analysis, and some understanding of the basics of Bayesian statistics, but little experience in its application. Graduate students of statistics and biostatistics will also find this book beneficial.
Michael Crawley J. Statistics. An Introduction Using R Michael Crawley J. Statistics. An Introduction Using R Новинка

Michael Crawley J. Statistics. An Introduction Using R

3524.28 руб.
"…I know of no better book of its kind…" (Journal of the Royal Statistical Society, Vol 169 (1), January 2006) A revised and updated edition of this bestselling introductory textbook to statistical analysis using the leading free software package R This new edition of a bestselling title offers a concise introduction to a broad array of statistical methods, at a level that is elementary enough to appeal to a wide range of disciplines. Step-by-step instructions help the non-statistician to fully understand the methodology. The book covers the full range of statistical techniques likely to be needed to analyse the data from research projects, including elementary material like t–tests and chi–squared tests, intermediate methods like regression and analysis of variance, and more advanced techniques like generalized linear modelling. Includes numerous worked examples and exercises within each chapter.
Michael Albers J. Introduction to Quantitative Data Analysis in the Behavioral and Social Sciences Michael Albers J. Introduction to Quantitative Data Analysis in the Behavioral and Social Sciences Новинка

Michael Albers J. Introduction to Quantitative Data Analysis in the Behavioral and Social Sciences

6744.78 руб.
Guides readers through the quantitative data analysis process including contextualizing data within a research situation, connecting data to the appropriate statistical tests, and drawing valid conclusions Introduction to Quantitative Data Analysis in the Behavioral and Social Sciences presents a clear and accessible introduction to the basics of quantitative data analysis and focuses on how to use statistical tests as a key tool for analyzing research data. The book presents the entire data analysis process as a cyclical, multiphase process and addresses the processes of exploratory analysis, decision-making for performing parametric or nonparametric analysis, and practical significance determination. In addition, the author details how data analysis is used to reveal the underlying patterns and relationships between the variables and connects those trends to the data’s contextual situation. Filling the gap in quantitative data analysis literature, this book teaches the methods and thought processes behind data analysis, rather than how to perform the study itself or how to perform individual statistical tests. With a clear and conversational style, readers are provided with a better understanding of the overall structure and methodology behind performing a data analysis as well as the needed techniques to make informed, meaningful decisions during data analysis. The book features numerous data analysis examples in order to emphasize the decision and thought processes that are best followed, and self-contained sections throughout separate the statistical data analysis from the detailed discussion of the concepts allowing readers to reference a specific section of the book for immediate solutions to problems and/or applications. Introduction to Quantitative Data Analysis in the Behavioral and Social Sciences also features coverage of the following: • The overall methodology and research mind-set for how to approach quantitative data analysis and how to use statistics tests as part of research data analysis • A comprehensive understanding of the data, its connection to a research situation, and the most appropriate statistical tests for the data • Numerous data analysis problems and worked-out examples to illustrate the decision and thought processes that reveal underlying patterns and trends • Detailed examples of the main concepts to aid readers in gaining the needed skills to perform a full analysis of research problems • A conversational tone to effectively introduce readers to the basics of how to perform data analysis as well as make meaningful decisions during data analysis Introduction to Quantitative Data Analysis in the Behavioral and Social Sciences is an ideal textbook for upper-undergraduate and graduate-level research method courses in the behavioral and social sciences, statistics, and engineering. This book is also an appropriate reference for practitioners who require a review of quantitative research methods. Michael J. Albers, Ph.D., is Professor in the Department of English at East Carolina University. His research interests include information design with a focus on answering real-world questions, the presentation of complex information, and human–information interaction. Dr. Albers received his Ph.D. in Technical Communication and Rhetoric from Texas Tech University.
Jean Salencon Yield Design Jean Salencon Yield Design Новинка

Jean Salencon Yield Design

8659.42 руб.
Since the middle of the 20th Century yield design approaches have been identified with the lower and upper bound theorem of limit analysis theory – a theory associated with perfect plasticity. This theory is very restrictive regarding the applicability of yield design approaches, which have been used for centuries for the stability of civil engineering structures. This book presents a theory of yield design within the original “equilibrium/resistance” framework rather than referring to the theories of plasticity or limit analysis; expressing the compatibility between the equilibrium of the considered structure and the resistance of its constituent material through simple mathematical arguments of duality and convex analysis results in a general formulation, which encompasses the many aspects of its implementation to various stability analysis problems. After a historic outline and an introductory example, the general theory is developed for the three-dimensional continuum model in a versatile form based upon simple arguments from the mathematical theory of convexity. It is then straightforwardly transposed to the one-dimensional curvilinear continuum, for the yield design analysis of beams, and the two-dimensional continuum model of plates and thin slabs subjected to bending. Field and laboratory observations of the collapse of mechanical systems are presented along with the defining concept of the multi-parameter loading mode. The compatibility of equilibrium and resistance is first expressed in its primal form, on the basis of the equilibrium equations and the strength domain of the material defined by a convex strength criterion along with the dual approach in the field of potentially safe loads, as is the highlighting of the role implicitly played by the theory of yield design as the fundamental basis of the implementation of the ultimate limit state design (ULSD) philosophy with the explicit introduction of resistance parameters. Contents 1. Origins and Topicality of a Concept. 2. An Introductory Example of the Yield Design Approach. 3. The Continuum Mechanics Framework. 4. Primal Approach of the Theory of Yield Design. 5. Dual Approach of the Theory of Yield Design. 6. Kinematic Exterior Approach. 7. Ultimate Limit State Design from the Theory of Yield Design. 8. Optimality and Probability Approaches of Yield Design. 9. Yield Design of Structures. 10. Yield Design of Plates: the Model. 11. Yield Design of Plates Subjected to Pure Bending. About the Authors Jean Salençon is Emeritus Professor at École polytechnique and École des ponts et chaussées, ParisTech, France. Since 2009 he has been a member of the Administrative Board of CNRS (Paris, France). He has received many awards including the Légion d’Honneur (Commander), Ordre National du Mérite (Officer) and Palmes Académiques (Commander). His research interests include structure analysis, soil mechanics and continuum mechanics.
James Schott R. Matrix Analysis for Statistics James Schott R. Matrix Analysis for Statistics Новинка

James Schott R. Matrix Analysis for Statistics

9372.7 руб.
An up-to-date version of the complete, self-contained introduction to matrix analysis theory and practice Providing accessible and in-depth coverage of the most common matrix methods now used in statistical applications, Matrix Analysis for Statistics, Third Edition features an easy-to-follow theorem/proof format. Featuring smooth transitions between topical coverage, the author carefully justifies the step-by-step process of the most common matrix methods now used in statistical applications, including eigenvalues and eigenvectors; the Moore-Penrose inverse; matrix differentiation; and the distribution of quadratic forms. An ideal introduction to matrix analysis theory and practice, Matrix Analysis for Statistics, Third Edition features: • New chapter or section coverage on inequalities, oblique projections, and antieigenvalues and antieigenvectors • Additional problems and chapter-end practice exercises at the end of each chapter • Extensive examples that are familiar and easy to understand • Self-contained chapters for flexibility in topic choice • Applications of matrix methods in least squares regression and the analyses of mean vectors and covariance matrices Matrix Analysis for Statistics, Third Edition is an ideal textbook for upper-undergraduate and graduate-level courses on matrix methods, multivariate analysis, and linear models. The book is also an excellent reference for research professionals in applied statistics. James R. Schott, PhD, is Professor in the Department of Statistics at the University of Central Florida. He has published numerous journal articles in the area of multivariate analysis. Dr. Schott’s research interests include multivariate analysis, analysis of covariance and correlation matrices, and dimensionality reduction techniques.
Rosaria Lombardo Correspondence Analysis. Theory, Practice and New Strategies Rosaria Lombardo Correspondence Analysis. Theory, Practice and New Strategies Новинка

Rosaria Lombardo Correspondence Analysis. Theory, Practice and New Strategies

8173.27 руб.
A comprehensive overview of the internationalisation of correspondence analysis Correspondence Analysis: Theory, Practice and New Strategies examines the key issues of correspondence analysis, and discusses the new advances that have been made over the last 20 years. The main focus of this book is to provide a comprehensive discussion of some of the key technical and practical aspects of correspondence analysis, and to demonstrate how they may be put to use. Particular attention is given to the history and mathematical links of the developments made. These links include not just those major contributions made by researchers in Europe (which is where much of the attention surrounding correspondence analysis has focused) but also the important contributions made by researchers in other parts of the world. Key features include: A comprehensive international perspective on the key developments of correspondence analysis. Discussion of correspondence analysis for nominal and ordinal categorical data. Discussion of correspondence analysis of contingency tables with varying association structures (symmetric and non-symmetric relationship between two or more categorical variables). Extensive treatment of many of the members of the correspondence analysis family for two-way, three-way and multiple contingency tables. Correspondence Analysis offers a comprehensive and detailed overview of this topic which will be of value to academics, postgraduate students and researchers wanting a better understanding of correspondence analysis. Readers interested in the historical development, internationalisation and diverse applicability of correspondence analysis will also find much to enjoy in this book.
Reinhard Viertl Statistical Methods for Fuzzy Data Reinhard Viertl Statistical Methods for Fuzzy Data Новинка

Reinhard Viertl Statistical Methods for Fuzzy Data

8885.48 руб.
Statistical data are not always precise numbers, or vectors, or categories. Real data are frequently what is called fuzzy. Examples where this fuzziness is obvious are quality of life data, environmental, biological, medical, sociological and economics data. Also the results of measurements can be best described by using fuzzy numbers and fuzzy vectors respectively. Statistical analysis methods have to be adapted for the analysis of fuzzy data. In this book, the foundations of the description of fuzzy data are explained, including methods on how to obtain the characterizing function of fuzzy measurement results. Furthermore, statistical methods are then generalized to the analysis of fuzzy data and fuzzy a-priori information. Key Features: Provides basic methods for the mathematical description of fuzzy data, as well as statistical methods that can be used to analyze fuzzy data. Describes methods of increasing importance with applications in areas such as environmental statistics and social science. Complements the theory with exercises and solutions and is illustrated throughout with diagrams and examples. Explores areas such quantitative description of data uncertainty and mathematical description of fuzzy data. This work is aimed at statisticians working with fuzzy logic, engineering statisticians, finance researchers, and environmental statisticians. It is written for readers who are familiar with elementary stochastic models and basic statistical methods.
Bendat Julius S. Random Data. Analysis and Measurement Procedures Bendat Julius S. Random Data. Analysis and Measurement Procedures Новинка

Bendat Julius S. Random Data. Analysis and Measurement Procedures

14176.92 руб.
A timely update of the classic book on the theory and application of random data analysis First published in 1971, Random Data served as an authoritative book on the analysis of experimental physical data for engineering and scientific applications. This Fourth Edition features coverage of new developments in random data management and analysis procedures that are applicable to a broad range of applied fields, from the aerospace and automotive industries to oceanographic and biomedical research. This new edition continues to maintain a balance of classic theory and novel techniques. The authors expand on the treatment of random data analysis theory, including derivations of key relationships in probability and random process theory. The book remains unique in its practical treatment of nonstationary data analysis and nonlinear system analysis, presenting the latest techniques on modern data acquisition, storage, conversion, and qualification of random data prior to its digital analysis. The Fourth Edition also includes: A new chapter on frequency domain techniques to model and identify nonlinear systems from measured input/output random data New material on the analysis of multiple-input/single-output linear models The latest recommended methods for data acquisition and processing of random data Important mathematical formulas to design experiments and evaluate results of random data analysis and measurement procedures Answers to the problem in each chapter Comprehensive and self-contained, Random Data, Fourth Edition is an indispensible book for courses on random data analysis theory and applications at the upper-undergraduate and graduate level. It is also an insightful reference for engineers and scientists who use statistical methods to investigate and solve problems with dynamic data.
Stephen Walters J. How to Design, Analyse and Report Cluster Randomised Trials in Medicine and Health Related Research Stephen Walters J. How to Design, Analyse and Report Cluster Randomised Trials in Medicine and Health Related Research Новинка

Stephen Walters J. How to Design, Analyse and Report Cluster Randomised Trials in Medicine and Health Related Research

7344.49 руб.
A complete guide to understanding cluster randomised trials Written by two researchers with extensive experience in the field, this book presents a complete guide to the design, analysis and reporting of cluster randomised trials. It spans a wide range of applications: trials in developing countries, trials in primary care, trials in the health services. A key feature is the use of R code and code from other popular packages to plan and analyse cluster trials, using data from actual trials. The book contains clear technical descriptions of the models used, and considers in detail the ethics involved in such trials and the problems in planning them. For readers and students who do not intend to run a trial but wish to be a critical reader of the literature, there are sections on the CONSORT statement, and exercises in reading published trials. Written in a clear, accessible style Features real examples taken from the authors’ extensive practitioner experience of designing and analysing clinical trials Demonstrates the use of R, Stata and SPSS for statistical analysis Includes computer code so the reader can replicate all the analyses Discusses neglected areas such as ethics and practical issues in running cluster randomised trials How to Design, Analyse and Report Cluster Randomised Trials in Medicine and Health Related Research provides an excellent reference tool and can be read with profit by statisticians, health services researchers, systematic reviewers and critical readers of cluster randomised trials.
Dr Logan Murray Biostatistical Design and Analysis Using R. A Practical Guide Dr Logan Murray Biostatistical Design and Analysis Using R. A Practical Guide Новинка

Dr Logan Murray Biostatistical Design and Analysis Using R. A Practical Guide

2139.84 руб.
R – the statistical and graphical environment is rapidly emerging as an important set of teaching and research tools for biologists. This book draws upon the popularity and free availability of R to couple the theory and practice of biostatistics into a single treatment, so as to provide a textbook for biologists learning statistics, R, or both. An abridged description of biostatistical principles and analysis sequence keys are combined together with worked examples of the practical use of R into a complete practical guide to designing and analyzing real biological research. Topics covered include: simple hypothesis testing, graphing exploratory data analysis and graphical summaries regression (linear, multi and non-linear) simple and complex ANOVA and ANCOVA designs (including nested, factorial, blocking, spit-plot and repeated measures) frequency analysis and generalized linear models. Linear mixed effects modeling is also incorporated extensively throughout as an alternative to traditional modeling techniques. The book is accompanied by a companion website www.wiley.com/go/logan/r with an extensive set of resources comprising all R scripts and data sets used in the book, additional worked examples, the biology package, and other instructional materials and links.
Okabe Atsuyuki Spatial Analysis Along Networks. Statistical and Computational Methods Okabe Atsuyuki Spatial Analysis Along Networks. Statistical and Computational Methods Новинка

Okabe Atsuyuki Spatial Analysis Along Networks. Statistical and Computational Methods

8965.94 руб.
In the real world, there are numerous and various events that occur on and alongside networks, including the occurrence of traffic accidents on highways, the location of stores alongside roads, the incidence of crime on streets and the contamination along rivers. In order to carry out analyses of those events, the researcher needs to be familiar with a range of specific techniques. Spatial Analysis Along Networks provides a practical guide to the necessary statistical techniques and their computational implementation. Each chapter illustrates a specific technique, from Stochastic Point Processes on a Network and Network Voronoi Diagrams, to Network K-function and Point Density Estimation Methods, and the Network Huff Model. The authors also discuss and illustrate the undertaking of the statistical tests described in a Geographical Information System (GIS) environment as well as demonstrating the user-friendly free software package SANET. Spatial Analysis Along Networks: Presents a much-needed practical guide to statistical spatial analysis of events on and alongside a network, in a logical, user-friendly order. Introduces the preliminary methods involved, before detailing the advanced, computational methods, enabling the readers a complete understanding of the advanced topics. Dedicates a separate chapter to each of the major techniques involved. Demonstrates the practicalities of undertaking the tests described in the book, using a GIS. Is supported by a supplementary website, providing readers with a link to the free software package SANET, so they can execute the statistical methods described in the book. Students and researchers studying spatial statistics, spatial analysis, geography, GIS, OR, traffic accident analysis, criminology, retail marketing, facility management and ecology will benefit from this book.
Robert Easterling G. Fundamentals of Statistical Experimental Design and Analysis Robert Easterling G. Fundamentals of Statistical Experimental Design and Analysis Новинка

Robert Easterling G. Fundamentals of Statistical Experimental Design and Analysis

6748.34 руб.
Professionals in all areas – business; government; the physical, life, and social sciences; engineering; medicine, etc. – benefit from using statistical experimental design to better understand their worlds and then use that understanding to improve the products, processes, and programs they are responsible for. This book aims to provide the practitioners of tomorrow with a memorable, easy to read, engaging guide to statistics and experimental design. This book uses examples, drawn from a variety of established texts, and embeds them in a business or scientific context, seasoned with a dash of humor, to emphasize the issues and ideas that led to the experiment and the what-do-we-do-next? steps after the experiment. Graphical data displays are emphasized as means of discovery and communication and formulas are minimized, with a focus on interpreting the results that software produce. The role of subject-matter knowledge, and passion, is also illustrated. The examples do not require specialized knowledge, and the lessons they contain are transferrable to other contexts. Fundamentals of Statistical Experimental Design and Analysis introduces the basic elements of an experimental design, and the basic concepts underlying statistical analyses. Subsequent chapters address the following families of experimental designs: Completely Randomized designs, with single or multiple treatment factors, quantitative or qualitative Randomized Block designs Latin Square designs Split-Unit designs Repeated Measures designs Robust designs Optimal designs Written in an accessible, student-friendly style, this book is suitable for a general audience and particularly for those professionals seeking to improve and apply their understanding of experimental design.
J. Verma P. Repeated Measures Design for Empirical Researchers J. Verma P. Repeated Measures Design for Empirical Researchers Новинка

J. Verma P. Repeated Measures Design for Empirical Researchers

9372.7 руб.
Introduces the applications of repeated measures design processes with the popular IBM® SPSS® software Repeated Measures Design for Empirical Researchers presents comprehensive coverage of the formation of research questions and the analysis of repeated measures using IBM SPSS and also includes the solutions necessary for understanding situations where the designs can be used. In addition to explaining the computation involved in each design, the book presents a unique discussion on how to conceptualize research problems as well as identify appropriate repeated measures designs for research purposes. Featuring practical examples from a multitude of domains including psychology, the social sciences, management, and sports science, the book helps readers better understand the associated theories and methodologies of repeated measures design processes. The book covers various fundamental concepts involved in the design of experiments, basic statistical designs, computational details, differentiating independent and repeated measures designs, and testing assumptions. Along with an introduction to IBM SPSS software, Repeated Measures Design for Empirical Researchers includes: A discussion of the popular repeated measures designs frequently used by researchers, such as one-way repeated measures ANOVA, two-way repeated measures design, two-way mixed design, and mixed design with two-way MANOVA Coverage of sample size determination for the successful implementation of designing and analyzing a repeated measures study A step-by-step guide to analyzing the data obtained with real-world examples throughout to illustrate the underlying advantages and assumptions A companion website with supplementary IBM SPSS data sets and programming solutions as well as additional case studies Repeated Measures Design for Empirical Researchers is a useful textbook for graduate- and PhD-level students majoring in biostatistics, the social sciences, psychology, medicine, management, sports, physical education, and health. The book is also an excellent reference for professionals interested in experimental designs and statistical sciences as well as statistical consultants and practitioners from other fields including biological, medical, agricultural, and horticultural sciences. J. P. Verma, PhD, is Professor of Statistics and Director of the Center for Advanced Studies at Lakshmibai National Institute of Physical Education, India. Professor Verma is an active researcher in sports modeling and data analysis and has conducted many workshops on research methodology, research designs, multivariate analysis, statistical modeling, and data analysis for students of management, physical education, social science, and economics. He is the author of Statistics for Exercise Science and Health with Microsoft® Office Excel®, also published by Wiley.
Murray Logan Biostatistical Design and Analysis Using R. A Practical Guide Murray Logan Biostatistical Design and Analysis Using R. A Practical Guide Новинка

Murray Logan Biostatistical Design and Analysis Using R. A Practical Guide

14842.65 руб.
R – the statistical and graphical environment is rapidly emerging as an important set of teaching and research tools for biologists. This book draws upon the popularity and free availability of R to couple the theory and practice of biostatistics into a single treatment, so as to provide a textbook for biologists learning statistics, R, or both. An abridged description of biostatistical principles and analysis sequence keys are combined together with worked examples of the practical use of R into a complete practical guide to designing and analyzing real biological research. Topics covered include: simple hypothesis testing, graphing exploratory data analysis and graphical summaries regression (linear, multi and non-linear) simple and complex ANOVA and ANCOVA designs (including nested, factorial, blocking, spit-plot and repeated measures) frequency analysis and generalized linear models. Linear mixed effects modeling is also incorporated extensively throughout as an alternative to traditional modeling techniques. The book is accompanied by a companion website www.wiley.com/go/logan/r with an extensive set of resources comprising all R scripts and data sets used in the book, additional worked examples, the biology package, and other instructional materials and links.
Jean-Marie Flaus Risk Analysis. Socio-technical and Industrial Systems Jean-Marie Flaus Risk Analysis. Socio-technical and Industrial Systems Новинка

Jean-Marie Flaus Risk Analysis. Socio-technical and Industrial Systems

13027.44 руб.
An overview of the methods used for risk analysis in a variety of industrial sectors, with a particular focus on the consideration of human aspects, this book provides a definition of all the fundamental notions associated with risks and risk management, as well as clearly placing the discipline of risk analysis within the broader context of risk management processes. The author begins by presenting a certain number of basic concepts, followed by the general principle of risk analysis. He then moves on to examine the ISO31000 standard, which provides a specification for the implementation of a risk management approach. The ability to represent the information we use is crucial, so the representation of knowledge, covering both information concerning the risk occurrence mechanism and details of the system under scrutiny, is also considered. The different analysis methods are then presented, firstly for the identification of risks, then for their analysis in terms of cause and effect, and finally for the implementation of safety measures. Concrete examples are given throughout the book and the methodology and method can be applied to various fields (industry, health, organization, technical systems). Contents Part 1. General Concepts and Principles 1. Introduction. 2. Basic Notions. 3. Principles of Risk Analysis Methods. 4. The Risk Management Process (ISO31000). Part 2. Knowledge Representation 5. Modeling Risk. 6. Measuring the Importance of a Risk. 7. Modeling of Systems for Risk Analysis. Part 3. Risk Analysis Method 8. Preliminary Hazard Analysis. 9. Failure Mode and Effects Analysis. 10. Deviation Analysis Using the HAZOP Method. 11. The Systemic and Organized Risk Analysis Method. 12. Fault Tree Analysis. 13. Event Tree and Bow-Tie Diagram Analysis. 14. Human Reliability Analysis. 15. Barrier Analysis and Layer of Protection Analysis. Part 4. Appendices Appendix 1. Occupational Hazard Checklists. Appendix 2. Causal Tree Analysis. Appendix 3. A Few Reminders on the Theory of Probability. Appendix 4. Useful Notions in Reliability Theory. Appendix 5. Data Sources for Reliability. Appendix 6. A Few Approaches for System Modelling. Appendix 7. CaseStudy: Chemical Process. Appendix 8. XRisk Software. About the Authors Jean-Marie Flaus is Professor at Joseph Fourier University in Grenoble, France.
N. Balakrishnan Methods and Applications of Statistics in Clinical Trials, Volume 2. Planning, Analysis, and Inferential Methods N. Balakrishnan Methods and Applications of Statistics in Clinical Trials, Volume 2. Planning, Analysis, and Inferential Methods Новинка

N. Balakrishnan Methods and Applications of Statistics in Clinical Trials, Volume 2. Planning, Analysis, and Inferential Methods

15067.45 руб.
Methods and Applications of Statistics in Clinical Trials, Volume 2: Planning, Analysis, and Inferential Methods includes updates of established literature from the Wiley Encyclopedia of Clinical Trials as well as original material based on the latest developments in clinical trials. Prepared by a leading expert, the second volume includes numerous contributions from current prominent experts in the field of medical research. In addition, the volume features: • Multiple new articles exploring emerging topics, such as evaluation methods with threshold, empirical likelihood methods, nonparametric ROC analysis, over- and under-dispersed models, and multi-armed bandit problems • Up-to-date research on the Cox proportional hazard model, frailty models, trial reports, intrarater reliability, conditional power, and the kappa index • Key qualitative issues including cost-effectiveness analysis, publication bias, and regulatory issues, which are crucial to the planning and data management of clinical trials
Christian Lalanne Mechanical Vibration and Shock Analysis, Random Vibration Christian Lalanne Mechanical Vibration and Shock Analysis, Random Vibration Новинка

Christian Lalanne Mechanical Vibration and Shock Analysis, Random Vibration

15517.06 руб.
The vast majority of vibrations encountered in the real environment are random in nature. Such vibrations are intrinsically complicated and this volume describes the process that enables us to simplify the required analysis, along with the analysis of the signal in the frequency domain. The power spectrum density is also defined, together with the requisite precautions to be taken in its calculations as well as the processes (windowing, overlapping) necessary to obtain improved results. An additional complementary method – the analysis of statistical properties of the time signal – is also described. This enables the distribution law of the maxima of a random Gaussian signal to be determined and simplifies the calculation of fatigue damage by avoiding direct peak counting.
Guosheng Yin Clinical Trial Design. Bayesian and Frequentist Adaptive Methods Guosheng Yin Clinical Trial Design. Bayesian and Frequentist Adaptive Methods Новинка

Guosheng Yin Clinical Trial Design. Bayesian and Frequentist Adaptive Methods

10115.42 руб.
A balanced treatment of the theories, methodologies, and design issues involved in clinical trials using statistical methods There has been enormous interest and development in Bayesian adaptive designs, especially for early phases of clinical trials. However, for phase III trials, frequentist methods still play a dominant role through controlling type I and type II errors in the hypothesis testing framework. From practical perspectives, Clinical Trial Design: Bayesian and Frequentist Adaptive Methods provides comprehensive coverage of both Bayesian and frequentist approaches to all phases of clinical trial design. Before underpinning various adaptive methods, the book establishes an overview of the fundamentals of clinical trials as well as a comparison of Bayesian and frequentist statistics. Recognizing that clinical trial design is one of the most important and useful skills in the pharmaceutical industry, this book provides detailed discussions on a variety of statistical designs, their properties, and operating characteristics for phase I, II, and III clinical trials as well as an introduction to phase IV trials. Many practical issues and challenges arising in clinical trials are addressed. Additional topics of coverage include: Risk and benefit analysis for toxicity and efficacy trade-offs Bayesian predictive probability trial monitoring Bayesian adaptive randomization Late onset toxicity and response Dose finding in drug combination trials Targeted therapy designs The author utilizes cutting-edge clinical trial designs and statistical methods that have been employed at the world's leading medical centers as well as in the pharmaceutical industry. The software used throughout the book is freely available on the book's related website, equipping readers with the necessary tools for designing clinical trials. Clinical Trial Design is an excellent book for courses on the topic at the graduate level. The book also serves as a valuable reference for statisticians and biostatisticians in the pharmaceutical industry as well as for researchers and practitioners who design, conduct, and monitor clinical trials in their everyday work.
Guosheng Yin Clinical Trial Design. Bayesian and Frequentist Adaptive Methods Guosheng Yin Clinical Trial Design. Bayesian and Frequentist Adaptive Methods Новинка

Guosheng Yin Clinical Trial Design. Bayesian and Frequentist Adaptive Methods

9897.71 руб.
A balanced treatment of the theories, methodologies, and design issues involved in clinical trials using statistical methods There has been enormous interest and development in Bayesian adaptive designs, especially for early phases of clinical trials. However, for phase III trials, frequentist methods still play a dominant role through controlling type I and type II errors in the hypothesis testing framework. From practical perspectives, Clinical Trial Design: Bayesian and Frequentist Adaptive Methods provides comprehensive coverage of both Bayesian and frequentist approaches to all phases of clinical trial design. Before underpinning various adaptive methods, the book establishes an overview of the fundamentals of clinical trials as well as a comparison of Bayesian and frequentist statistics. Recognizing that clinical trial design is one of the most important and useful skills in the pharmaceutical industry, this book provides detailed discussions on a variety of statistical designs, their properties, and operating characteristics for phase I, II, and III clinical trials as well as an introduction to phase IV trials. Many practical issues and challenges arising in clinical trials are addressed. Additional topics of coverage include: Risk and benefit analysis for toxicity and efficacy trade-offs Bayesian predictive probability trial monitoring Bayesian adaptive randomization Late onset toxicity and response Dose finding in drug combination trials Targeted therapy designs The author utilizes cutting-edge clinical trial designs and statistical methods that have been employed at the world's leading medical centers as well as in the pharmaceutical industry. The software used throughout the book is freely available on the book's related website, equipping readers with the necessary tools for designing clinical trials. Clinical Trial Design is an excellent book for courses on the topic at the graduate level. The book also serves as a valuable reference for statisticians and biostatisticians in the pharmaceutical industry as well as for researchers and practitioners who design, conduct, and monitor clinical trials in their everyday work.
Pawlowsky-Glahn Vera Compositional Data Analysis. Theory and Applications Pawlowsky-Glahn Vera Compositional Data Analysis. Theory and Applications Новинка

Pawlowsky-Glahn Vera Compositional Data Analysis. Theory and Applications

9349.1 руб.
It is difficult to imagine that the statistical analysis of compositional data has been a major issue of concern for more than 100 years. It is even more difficult to realize that so many statisticians and users of statistics are unaware of the particular problems affecting compositional data, as well as their solutions. The issue of ``spurious correlation'', as the situation was phrased by Karl Pearson back in 1897, affects all data that measures parts of some whole, such as percentages, proportions, ppm and ppb. Such measurements are present in all fields of science, ranging from geology, biology, environmental sciences, forensic sciences, medicine and hydrology. This book presents the history and development of compositional data analysis along with Aitchison's log-ratio approach. Compositional Data Analysis describes the state of the art both in theoretical fields as well as applications in the different fields of science. Key Features: Reflects the state-of-the-art in compositional data analysis. Gives an overview of the historical development of compositional data analysis, as well as basic concepts and procedures. Looks at advances in algebra and calculus on the simplex. Presents applications in different fields of science, including, genomics, ecology, biology, geochemistry, planetology, chemistry and economics. Explores connections to correspondence analysis and the Dirichlet distribution. Presents a summary of three available software packages for compositional data analysis. Supported by an accompanying website featuring R code. Applied scientists working on compositional data analysis in any field of science, both in academia and professionals will benefit from this book, along with graduate students in any field of science working with compositional data.
Csaba Ortutay Molecular Data Analysis Using R Csaba Ortutay Molecular Data Analysis Using R Новинка

Csaba Ortutay Molecular Data Analysis Using R

7494.6 руб.
This book addresses the difficulties experienced by wet lab researchers with the statistical analysis of molecular biology related data. The authors explain how to use R and Bioconductor for the analysis of experimental data in the field of molecular biology. The content is based upon two university courses for bioinformatics and experimental biology students (Biological Data Analysis with R and High-throughput Data Analysis with R). The material is divided into chapters based upon the experimental methods used in the laboratories. Key features include: • Broad appeal–the authors target their material to researchers in several levels, ensuring that the basics are always covered. • First book to explain how to use R and Bioconductor for the analysis of several types of experimental data in the field of molecular biology. • Focuses on R and Bioconductor, which are widely used for data analysis. One great benefit of R and Bioconductor is that there is a vast user community and very active discussion in place, in addition to the practice of sharing codes. Further, R is the platform for implementing new analysis approaches, therefore novel methods are available early for R users.
Galit Shmueli Information Quality. The Potential of Data and Analytics to Generate Knowledge Galit Shmueli Information Quality. The Potential of Data and Analytics to Generate Knowledge Новинка

Galit Shmueli Information Quality. The Potential of Data and Analytics to Generate Knowledge

6748.34 руб.
Provides an important framework for data analysts in assessing the quality of data and its potential to provide meaningful insights through analysis Analytics and statistical analysis have become pervasive topics, mainly due to the growing availability of data and analytic tools. Technology, however, fails to deliver insights with added value if the quality of the information it generates is not assured. Information Quality (InfoQ) is a tool developed by the authors to assess the potential of a dataset to achieve a goal of interest, using data analysis. Whether the information quality of a dataset is sufficient is of practical importance at many stages of the data analytics journey, from the pre-data collection stage to the post-data collection and post-analysis stages. It is also critical to various stakeholders: data collection agencies, analysts, data scientists, and management. This book: Explains how to integrate the notions of goal, data, analysis and utility that are the main building blocks of data analysis within any domain. Presents a framework for integrating domain knowledge with data analysis. Provides a combination of both methodological and practical aspects of data analysis. Discusses issues surrounding the implementation and integration of InfoQ in both academic programmes and business / industrial projects. Showcases numerous case studies in a variety of application areas such as education, healthcare, official statistics, risk management and marketing surveys. Presents a review of software tools from the InfoQ perspective along with example datasets on an accompanying website. This book will be beneficial for researchers in academia and in industry, analysts, consultants, and agencies that collect and analyse data as well as undergraduate and postgraduate courses involving data analysis.
Mike Cheung W.-L. Meta-Analysis. A Structural Equation Modeling Approach Mike Cheung W.-L. Meta-Analysis. A Structural Equation Modeling Approach Новинка

Mike Cheung W.-L. Meta-Analysis. A Structural Equation Modeling Approach

4609.87 руб.
Presents a novel approach to conducting meta-analysis using structural equation modeling. Structural equation modeling (SEM) and meta-analysis are two powerful statistical methods in the educational, social, behavioral, and medical sciences. They are often treated as two unrelated topics in the literature. This book presents a unified framework on analyzing meta-analytic data within the SEM framework, and illustrates how to conduct meta-analysis using the metaSEM package in the R statistical environment. Meta-Analysis: A Structural Equation Modeling Approach begins by introducing the importance of SEM and meta-analysis in answering research questions. Key ideas in meta-analysis and SEM are briefly reviewed, and various meta-analytic models are then introduced and linked to the SEM framework. Fixed-, random-, and mixed-effects models in univariate and multivariate meta-analyses, three-level meta-analysis, and meta-analytic structural equation modeling, are introduced. Advanced topics, such as using restricted maximum likelihood estimation method and handling missing covariates, are also covered. Readers will learn a single framework to apply both meta-analysis and SEM. Examples in R and in Mplus are included. This book will be a valuable resource for statistical and academic researchers and graduate students carrying out meta-analyses, and will also be useful to researchers and statisticians using SEM in biostatistics. Basic knowledge of either SEM or meta-analysis will be helpful in understanding the materials in this book.

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Guides readers through the quantitative data analysis process including contextualizing data within a research situation, connecting data to the appropriate statistical tests, and drawing valid conclusions Introduction to Quantitative Data Analysis in the Behavioral and Social Sciences presents a clear and accessible introduction to the basics of quantitative data analysis and focuses on how to use statistical tests as a key tool for analyzing research data. The book presents the entire data analysis process as a cyclical, multiphase process and addresses the processes of exploratory analysis, decision-making for performing parametric or nonparametric analysis, and practical significance determination. In addition, the author details how data analysis is used to reveal the underlying patterns and relationships between the variables and connects those trends to the data’s contextual situation. Filling the gap in quantitative data analysis literature, this book teaches the methods and thought processes behind data analysis, rather than how to perform the study itself or how to perform individual statistical tests. With a clear and conversational style, readers are provided with a better understanding of the overall structure and methodology behind performing a data analysis as well as the needed techniques to make informed, meaningful decisions during data analysis. The book features numerous data analysis examples in order to emphasize the decision and thought processes that are best followed, and self-contained sections throughout separate the statistical data analysis from the detailed discussion of the concepts allowing readers to reference a specific section of the book for immediate solutions to problems and/or applications. Introduction to Quantitative Data Analysis in the Behavioral and Social Sciences also features coverage of the following: • The overall methodology and research mind-set for how to approach quantitative data analysis and how to use statistics tests as part of research data analysis • A comprehensive understanding of the data, its connection to a research situation, and the most appropriate statistical tests for the data • Numerous data analysis problems and worked-out examples to illustrate the decision and thought processes that reveal underlying patterns and trends • Detailed examples of the main concepts to aid readers in gaining the needed skills to perform a full analysis of research problems • A conversational tone to effectively introduce readers to the basics of how to perform data analysis as well as make meaningful decisions during data analysis Introduction to Quantitative Data Analysis in the Behavioral and Social Sciences is an ideal textbook for upper-undergraduate and graduate-level research method courses in the behavioral and social sciences, statistics, and engineering. This book is also an appropriate reference for practitioners who require a review of quantitative research methods. Michael J. Albers, Ph.D., is Professor in the Department of English at East Carolina University. His research interests include information design with a focus on answering real-world questions, the presentation of complex information, and human–information interaction. Dr. Albers received his Ph.D. in Technical Communication and Rhetoric from Texas Tech University.
Продажа statistical analysis of regional yield trials ammi analysis of factorial designs лучших цены всего мира
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