application of longitudinal data analysis on fbs of adult diabetes



Yuichi Motai Data-Variant Kernel Analysis Yuichi Motai Data-Variant Kernel Analysis Новинка

Yuichi Motai Data-Variant Kernel Analysis

9748.31 руб.
Describes and discusses the variants of kernel analysis methods for data types that have been intensely studied in recent years This book covers kernel analysis topics ranging from the fundamental theory of kernel functions to its applications. The book surveys the current status, popular trends, and developments in kernel analysis studies. The author discusses multiple kernel learning algorithms and how to choose the appropriate kernels during the learning phase. Data-Variant Kernel Analysis is a new pattern analysis framework for different types of data configurations. The chapters include data formations of offline, distributed, online, cloud, and longitudinal data, used for kernel analysis to classify and predict future state. Data-Variant Kernel Analysis: Surveys the kernel analysis in the traditionally developed machine learning techniques, such as Neural Networks (NN), Support Vector Machines (SVM), and Principal Component Analysis (PCA) Develops group kernel analysis with the distributed databases to compare speed and memory usages Explores the possibility of real-time processes by synthesizing offline and online databases Applies the assembled databases to compare cloud computing environments Examines the prediction of longitudinal data with time-sequential configurations Data-Variant Kernel Analysis is a detailed reference for graduate students as well as electrical and computer engineers interested in pattern analysis and its application in colon cancer detection.
Sabine Landau Cluster Analysis Sabine Landau Cluster Analysis Новинка

Sabine Landau Cluster Analysis

7123.25 руб.
Cluster analysis comprises a range of methods for classifying multivariate data into subgroups. By organizing multivariate data into such subgroups, clustering can help reveal the characteristics of any structure or patterns present. These techniques have proven useful in a wide range of areas such as medicine, psychology, market research and bioinformatics. This fifth edition of the highly successful Cluster Analysis includes coverage of the latest developments in the field and a new chapter dealing with finite mixture models for structured data. Real life examples are used throughout to demonstrate the application of the theory, and figures are used extensively to illustrate graphical techniques. The book is comprehensive yet relatively non-mathematical, focusing on the practical aspects of cluster analysis. Key Features: • Presents a comprehensive guide to clustering techniques, with focus on the practical aspects of cluster analysis. • Provides a thorough revision of the fourth edition, including new developments in clustering longitudinal data and examples from bioinformatics and gene studies • Updates the chapter on mixture models to include recent developments and presents a new chapter on mixture modeling for structured data. Practitioners and researchers working in cluster analysis and data analysis will benefit from this book.
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.
Hyunjoung Lee Fundamentals of Big Data Network Analysis for Research and Industry Hyunjoung Lee Fundamentals of Big Data Network Analysis for Research and Industry Новинка

Hyunjoung Lee Fundamentals of Big Data Network Analysis for Research and Industry

4609.87 руб.
Fundamentals of Big Data Network Analysis for Research and Industry Hyunjoung Lee, Institute of Green Technology, Yonsei University, Republic of Korea Il Sohn, Material Science and Engineering, Yonsei University, Republic of Korea Presents the methodology of big data analysis using examples from research and industry There are large amounts of data everywhere, and the ability to pick out crucial information is increasingly important. Contrary to popular belief, not all information is useful; big data network analysis assumes that data is not only large, but also meaningful, and this book focuses on the fundamental techniques required to extract essential information from vast datasets. Featuring case studies drawn largely from the iron and steel industries, this book offers practical guidance which will enable readers to easily understand big data network analysis. Particular attention is paid to the methodology of network analysis, offering information on the method of data collection, on research design and analysis, and on the interpretation of results. A variety of programs including UCINET, NetMiner, R, NodeXL, and Gephi for network analysis are covered in detail. Fundamentals of Big Data Network Analysis for Research and Industry looks at big data from a fresh perspective, and provides a new approach to data analysis. This book: Explains the basic concepts in understanding big data and filtering meaningful data Presents big data analysis within the networking perspective Features methodology applicable to research and industry Describes in detail the social relationship between big data and its implications Provides insight into identifying patterns and relationships between seemingly unrelated big data Fundamentals of Big Data Network Analysis for Research and Industry will prove a valuable resource for analysts, research engineers, industrial engineers, marketing professionals, and any individuals dealing with accumulated large data whose interest is to analyze and identify potential relationships among data sets.
Xiao-Hua Zhou Applied Missing Data Analysis in the Health Sciences Xiao-Hua Zhou Applied Missing Data Analysis in the Health Sciences Новинка

Xiao-Hua Zhou Applied Missing Data Analysis in the Health Sciences

8247.97 руб.
A modern and practical guide to the essential concepts and ideas for analyzing data with missing observations in the field of biostatistics With an emphasis on hands-on applications, Applied Missing Data Analysis in the Health Sciences outlines the various modern statistical methods for the analysis of missing data. The authors acknowledge the limitations of established techniques and provide newly-developed methods with concrete applications in areas such as causal inference methods and the field of diagnostic medicine. Organized by types of data, chapter coverage begins with an overall introduction to the existence and limitations of missing data and continues into traditional techniques for missing data inference, including likelihood-based, weighted GEE, multiple imputation, and Bayesian methods. The book’s subsequently covers cross-sectional, longitudinal, hierarchical, survival data. In addition, Applied Missing Data Analysis in the Health Sciences features: Multiple data sets that can be replicated using the SAS®, Stata®, R, and WinBUGS software packages Numerous examples of case studies in the field of biostatistics to illustrate real-world scenarios and demonstrate applications of discussed methodologies Detailed appendices to guide readers through the use of the presented data in various software environments Applied Missing Data Analysis in the Health Sciences is an excellent textbook for upper-undergraduate and graduate-level biostatistics courses as well as an ideal resource for health science researchers and applied statisticians.
Vera Pawlowsky-Glahn Modeling and Analysis of Compositional Data Vera Pawlowsky-Glahn Modeling and Analysis of Compositional Data Новинка

Vera Pawlowsky-Glahn Modeling and Analysis of Compositional Data

8173.27 руб.
Modeling and Analysis of Compositional Data presents a practical and comprehensive introduction to the analysis of compositional data along with numerous examples to illustrate both theory and application of each method. Based upon short courses delivered by the authors, it provides a complete and current compendium of fundamental to advanced methodologies along with exercises at the end of each chapter to improve understanding, as well as data and a solutions manual which is available on an accompanying website. Complementing Pawlowsky-Glahn’s earlier collective text that provides an overview of the state-of-the-art in this field, Modeling and Analysis of Compositional Data fills a gap in the literature for a much-needed manual for teaching, self learning or consulting.
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.
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.
Daniel Larose T. Discovering Knowledge in Data. An Introduction to Data Mining Daniel Larose T. Discovering Knowledge in Data. An Introduction to Data Mining Новинка

Daniel Larose T. Discovering Knowledge in Data. An Introduction to Data Mining

7122.94 руб.
The field of data mining lies at the confluence of predictive analytics, statistical analysis, and business intelligence. Due to the ever-increasing complexity and size of data sets and the wide range of applications in computer science, business, and health care, the process of discovering knowledge in data is more relevant than ever before. This book provides the tools needed to thrive in today’s big data world. The author demonstrates how to leverage a company’s existing databases to increase profits and market share, and carefully explains the most current data science methods and techniques. The reader will “learn data mining by doing data mining”. By adding chapters on data modelling preparation, imputation of missing data, and multivariate statistical analysis, Discovering Knowledge in Data, Second Edition remains the eminent reference on data mining. The second edition of a highly praised, successful reference on data mining, with thorough coverage of big data applications, predictive analytics, and statistical analysis. Includes new chapters on Multivariate Statistics, Preparing to Model the Data, and Imputation of Missing Data, and an Appendix on Data Summarization and Visualization Offers extensive coverage of the R statistical programming language Contains 280 end-of-chapter exercises Includes a companion website for university instructors who adopt the book
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
Harvey Goldstein Methodological Developments in Data Linkage Harvey Goldstein Methodological Developments in Data Linkage Новинка

Harvey Goldstein Methodological Developments in Data Linkage

6658.7 руб.
A comprehensive compilation of new developments in data linkage methodology The increasing availability of large administrative databases has led to a dramatic rise in the use of data linkage, yet the standard texts on linkage are still those which describe the seminal work from the 1950-60s, with some updates. Linkage and analysis of data across sources remains problematic due to lack of discriminatory and accurate identifiers, missing data and regulatory issues. Recent developments in data linkage methodology have concentrated on bias and analysis of linked data, novel approaches to organising relationships between databases and privacy-preserving linkage. Methodological Developments in Data Linkage brings together a collection of contributions from members of the international data linkage community, covering cutting edge methodology in this field. It presents opportunities and challenges provided by linkage of large and often complex datasets, including analysis problems, legal and security aspects, models for data access and the development of novel research areas. New methods for handling uncertainty in analysis of linked data, solutions for anonymised linkage and alternative models for data collection are also discussed. Key Features: Presents cutting edge methods for a topic of increasing importance to a wide range of research areas, with applications to data linkage systems internationally Covers the essential issues associated with data linkage today Includes examples based on real data linkage systems, highlighting the opportunities, successes and challenges that the increasing availability of linkage data provides Novel approach incorporates technical aspects of both linkage, management and analysis of linked data This book will be of core interest to academics, government employees, data holders, data managers, analysts and statisticians who use administrative data. It will also appeal to researchers in a variety of areas, including epidemiology, biostatistics, social statistics, informatics, policy and public health.
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.
Carpenter James Multiple Imputation and its Application Carpenter James Multiple Imputation and its Application Новинка

Carpenter James Multiple Imputation and its Application

6207.19 руб.
A practical guide to analysing partially observed data. Collecting, analysing and drawing inferences from data is central to research in the medical and social sciences. Unfortunately, it is rarely possible to collect all the intended data. The literature on inference from the resulting incomplete data is now huge, and continues to grow both as methods are developed for large and complex data structures, and as increasing computer power and suitable software enable researchers to apply these methods. This book focuses on a particular statistical method for analysing and drawing inferences from incomplete data, called Multiple Imputation (MI). MI is attractive because it is both practical and widely applicable. The authors aim is to clarify the issues raised by missing data, describing the rationale for MI, the relationship between the various imputation models and associated algorithms and its application to increasingly complex data structures. Multiple Imputation and its Application: Discusses the issues raised by the analysis of partially observed data, and the assumptions on which analyses rest. Presents a practical guide to the issues to consider when analysing incomplete data from both observational studies and randomized trials. Provides a detailed discussion of the practical use of MI with real-world examples drawn from medical and social statistics. Explores handling non-linear relationships and interactions with multiple imputation, survival analysis, multilevel multiple imputation, sensitivity analysis via multiple imputation, using non-response weights with multiple imputation and doubly robust multiple imputation. Multiple Imputation and its Application is aimed at quantitative researchers and students in the medical and social sciences with the aim of clarifying the issues raised by the analysis of incomplete data data, outlining the rationale for MI and describing how to consider and address the issues that arise in its application.
Daniel Denis J. SPSS Data Analysis for Univariate, Bivariate, and Multivariate Statistics Daniel Denis J. SPSS Data Analysis for Univariate, Bivariate, and Multivariate Statistics Новинка

Daniel Denis J. SPSS Data Analysis for Univariate, Bivariate, and Multivariate Statistics

7982.5 руб.
Enables readers to start doing actual data analysis fast for a truly hands-on learning experience This concise and very easy-to-use primer introduces readers to a host of computational tools useful for making sense out of data, whether that data come from the social, behavioral, or natural sciences. The book places great emphasis on both data analysis and drawing conclusions from empirical observations. It also provides formulas where needed in many places, while always remaining focused on concepts rather than mathematical abstraction. SPSS Data Analysis for Univariate, Bivariate, and Multivariate Statistics offers a variety of popular statistical analyses and data management tasks using SPSS that readers can immediately apply as needed for their own research, and emphasizes many helpful computational tools used in the discovery of empirical patterns. The book begins with a review of essential statistical principles before introducing readers to SPSS. The book then goes on to offer chapters on: Exploratory Data Analysis, Basic Statistics, and Visual Displays; Data Management in SPSS; Inferential Tests on Correlations, Counts, and Means; Power Analysis and Estimating Sample Size; Analysis of Variance – Fixed and Random Effects; Repeated Measures ANOVA; Simple and Multiple Linear Regression; Logistic Regression; Multivariate Analysis of Variance (MANOVA) and Discriminant Analysis; Principal Components Analysis; Exploratory Factor Analysis; and Non-Parametric Tests. This helpful resource allows readers to: Understand data analysis in practice rather than delving too deeply into abstract mathematical concepts Make use of computational tools used by data analysis professionals. Focus on real-world application to apply concepts from the book to actual research Assuming only minimal, prior knowledge of statistics, SPSS Data Analysis for Univariate, Bivariate, and Multivariate Statistics is an excellent “how-to” book for undergraduate and graduate students alike. This book is also a welcome resource for researchers and professionals who require a quick, go-to source for performing essential statistical analyses and data management tasks.
E. Ferrannini International Textbook of Diabetes Mellitus E. Ferrannini International Textbook of Diabetes Mellitus Новинка

E. Ferrannini International Textbook of Diabetes Mellitus

29989.78 руб.
The International Textbook of Diabetes Mellitus has been a successful, well-respected medical textbook for almost 20 years, over 3 editions. Encyclopaedic and international in scope, the textbook covers all aspects of diabetes ensuring a truly multidisciplinary and global approach. Sections covered include epidemiology, diagnosis, pathogenesis, management and complications of diabetes and public health issues worldwide. It incorporates a vast amount of new data regarding the scientific understanding and clinical management of this disease, with each new edition always reflecting the substantial advances in the field. Whereas other diabetes textbooks are primarily clinical with less focus on the basic science behind diabetes, ITDM's primary philosophy has always been to comprehensively cover the basic science of metabolism, linking this closely to the pathophysiology and clinical aspects of the disease. Edited by four world-famous diabetes specialists, the book is divided into 13 sections, each section edited by a section editor of major international prominence. As well as covering all aspects of diabetes, from epidemiology and pathophysiology to the management of the condition and the complications that arise, this fourth edition also includes two new sections on NAFLD, NASH and non-traditional associations with diabetes, and clinical trial evidence in diabetes. This fourth edition of an internationally recognised textbook will once again provide all those involved in diabetes research and development, as well as diabetes specialists with the most comprehensive scientific reference book on diabetes available.
Hannu Oja Robust Correlation. Theory and Applications Hannu Oja Robust Correlation. Theory and Applications Новинка

Hannu Oja Robust Correlation. Theory and Applications

6658.7 руб.
This bookpresents material on both the analysis of the classical concepts of correlation and on the development of their robust versions, as well as discussing the related concepts of correlation matrices, partial correlation, canonical correlation, rank correlations, with the corresponding robust and non-robust estimation procedures. Every chapter contains a set of examples with simulated and real-life data. Key features: Makes modern and robust correlation methods readily available and understandable to practitioners, specialists, and consultants working in various fields. Focuses on implementation of methodology and application of robust correlation with R. Introduces the main approaches in robust statistics, such as Huber’s minimax approach and Hampel’s approach based on influence functions. Explores various robust estimates of the correlation coefficient including the minimax variance and bias estimates as well as the most B- and V-robust estimates. Contains applications of robust correlation methods to exploratory data analysis, multivariate statistics, statistics of time series, and to real-life data. Includes an accompanying website featuring computer code and datasets Features exercises and examples throughout the text using both small and large data sets. Theoretical and applied statisticians, specialists in multivariate statistics, robust statistics, robust time series analysis, data analysis and signal processing will benefit from this book. Practitioners who use correlation based methods in their work as well as postgraduate students in statistics will also find this book useful.
Dhammika Amaratunga Exploration and Analysis of DNA Microarray and Other High-Dimensional Data Dhammika Amaratunga Exploration and Analysis of DNA Microarray and Other High-Dimensional Data Новинка

Dhammika Amaratunga Exploration and Analysis of DNA Microarray and Other High-Dimensional Data

9598.21 руб.
Praise for the First Edition “…extremely well written…a comprehensive and up-to-date overview of this important field.” – Journal of Environmental Quality Exploration and Analysis of DNA Microarray and Other High-Dimensional Data, Second Edition provides comprehensive coverage of recent advancements in microarray data analysis. A cutting-edge guide, the Second Edition demonstrates various methodologies for analyzing data in biomedical research and offers an overview of the modern techniques used in microarray technology to study patterns of gene activity. The new edition answers the need for an efficient outline of all phases of this revolutionary analytical technique, from preprocessing to the analysis stage. Utilizing research and experience from highly-qualified authors in fields of data analysis, Exploration and Analysis of DNA Microarray and Other High-Dimensional Data, Second Edition features: A new chapter on the interpretation of findings that includes a discussion of signatures and material on gene set analysis, including network analysis New topics of coverage including ABC clustering, biclustering, partial least squares, penalized methods, ensemble methods, and enriched ensemble methods Updated exercises to deepen knowledge of the presented material and provide readers with resources for further study The book is an ideal reference for scientists in biomedical and genomics research fields who analyze DNA microarrays and protein array data, as well as statisticians and bioinformatics practitioners. Exploration and Analysis of DNA Microarray and Other High-Dimensional Data, Second Edition is also a useful text for graduate-level courses on statistics, computational biology, and bioinformatics.
Mourad Elloumi Biological Knowledge Discovery Handbook. Preprocessing, Mining and Postprocessing of Biological Data Mourad Elloumi Biological Knowledge Discovery Handbook. Preprocessing, Mining and Postprocessing of Biological Data Новинка

Mourad Elloumi Biological Knowledge Discovery Handbook. Preprocessing, Mining and Postprocessing of Biological Data

14021.69 руб.
The first comprehensive overview of preprocessing, mining, and postprocessing of biological data Molecular biology is undergoing exponential growth in both the volume and complexity of biological data—and knowledge discovery offers the capacity to automate complex search and data analysis tasks. This book presents a vast overview of the most recent developments on techniques and approaches in the field of biological knowledge discovery and data mining (KDD)—providing in-depth fundamental and technical field information on the most important topics encountered. Written by top experts, Biological Knowledge Discovery Handbook: Preprocessing, Mining, and Postprocessing of Biological Data covers the three main phases of knowledge discovery (data preprocessing, data processing—also known as data mining—and data postprocessing) and analyzes both verification systems and discovery systems. BIOLOGICAL DATA PREPROCESSING Part A: Biological Data Management Part B: Biological Data Modeling Part C: Biological Feature Extraction Part D Biological Feature Selection BIOLOGICAL DATA MINING Part E: Regression Analysis of Biological Data Part F Biological Data Clustering Part G: Biological Data Classification Part H: Association Rules Learning from Biological Data Part I: Text Mining and Application to Biological Data Part J: High-Performance Computing for Biological Data Mining Combining sound theory with practical applications in molecular biology, Biological Knowledge Discovery Handbook is ideal for courses in bioinformatics and biological KDD as well as for practitioners and professional researchers in computer science, life science, and mathematics.
Alan Agresti Analysis of Ordinal Categorical Data Alan Agresti Analysis of Ordinal Categorical Data Новинка

Alan Agresti Analysis of Ordinal Categorical Data

11571.43 руб.
Statistical science’s first coordinated manual of methods for analyzing ordered categorical data, now fully revised and updated, continues to present applications and case studies in fields as diverse as sociology, public health, ecology, marketing, and pharmacy. Analysis of Ordinal Categorical Data, Second Edition provides an introduction to basic descriptive and inferential methods for categorical data, giving thorough coverage of new developments and recent methods. Special emphasis is placed on interpretation and application of methods including an integrated comparison of the available strategies for analyzing ordinal data. Practitioners of statistics in government, industry (particularly pharmaceutical), and academia will want this new edition.
Rudis Bob Data-Driven Security. Analysis, Visualization and Dashboards Rudis Bob Data-Driven Security. Analysis, Visualization and Dashboards Новинка

Rudis Bob Data-Driven Security. Analysis, Visualization and Dashboards

3831.6 руб.
Uncover hidden patterns of data and respond with countermeasures Security professionals need all the tools at their disposal to increase their visibility in order to prevent security breaches and attacks. This careful guide explores two of the most powerful ? data analysis and visualization. You'll soon understand how to harness and wield data, from collection and storage to management and analysis as well as visualization and presentation. Using a hands-on approach with real-world examples, this book shows you how to gather feedback, measure the effectiveness of your security methods, and make better decisions. Everything in this book will have practical application for information security professionals. Helps IT and security professionals understand and use data, so they can thwart attacks and understand and visualize vulnerabilities in their networks Includes more than a dozen real-world examples and hands-on exercises that demonstrate how to analyze security data and intelligence and translate that information into visualizations that make plain how to prevent attacks Covers topics such as how to acquire and prepare security data, use simple statistical methods to detect malware, predict rogue behavior, correlate security events, and more Written by a team of well-known experts in the field of security and data analysis Lock down your networks, prevent hacks, and thwart malware by improving visibility into the environment, all through the power of data and Security Using Data Analysis, Visualization, and Dashboards.
Hale Robert Time Series Analysis in Meteorology and Climatology. An Introduction Hale Robert Time Series Analysis in Meteorology and Climatology. An Introduction Новинка

Hale Robert Time Series Analysis in Meteorology and Climatology. An Introduction

8502.32 руб.
Time Series Analysis in Meteorology and Climatology provides an accessible overview of this notoriously difficult subject. Clearly structured throughout, the authors develop sufficient theoretical foundation to understand the basis for applying various analytical methods to a time series and show clearly how to interpret the results. Taking a unique approach to the subject, the authors use a combination of theory and application to real data sets to enhance student understanding throughout the book. This book is written for those students that have a data set in the form of a time series and are confronted with the problem of how to analyse this data. Each chapter covers the various methods that can be used to carry out this analysis with coverage of the necessary theory and its application. In the theoretical section topics covered include; the mathematical origin of spectrum windows, leakage of variance and understanding spectrum windows. The applications section includes real data sets for students to analyse. Scalar variables are used for ease of understanding for example air temperatures, wind speed and precipitation. Students are encouraged to write their own computer programmes and data sets are provided to enable them to recognize quickly whether their programme is working correctly- one data set is provided with artificial data and the other with real data where the students are required to physically interpret the results of their periodgram analysis. Based on the acclaimed and long standing course at the University of Oklahoma and part of the RMetS Advancing Weather and Climate Science Series, this book is distinct in its approach to the subject matter in that it is written specifically for readers in meteorology and climatology and uses a mix of theory and application to real data sets.
Collins Linda M. Latent Class and Latent Transition Analysis. With Applications in the Social, Behavioral, and Health Sciences Collins Linda M. Latent Class and Latent Transition Analysis. With Applications in the Social, Behavioral, and Health Sciences Новинка

Collins Linda M. Latent Class and Latent Transition Analysis. With Applications in the Social, Behavioral, and Health Sciences

10115.42 руб.
A modern, comprehensive treatment of latent class and latent transition analysis for categorical data On a daily basis, researchers in the social, behavioral, and health sciences collect information and fit statistical models to the gathered empirical data with the goal of making significant advances in these fields. In many cases, it can be useful to identify latent, or unobserved, subgroups in a population, where individuals' subgroup membership is inferred from their responses on a set of observed variables. Latent Class and Latent Transition Analysis provides a comprehensive and unified introduction to this topic through one-of-a-kind, step-by-step presentations and coverage of theoretical, technical, and practical issues in categorical latent variable modeling for both cross-sectional and longitudinal data. The book begins with an introduction to latent class and latent transition analysis for categorical data. Subsequent chapters delve into more in-depth material, featuring: A complete treatment of longitudinal latent class models Focused coverage of the conceptual underpinnings of interpretation and evaluationof a latent class solution Use of parameter restrictions and detection of identification problems Advanced topics such as multi-group analysis and the modeling and interpretation of interactions between covariates The authors present the topic in a style that is accessible yet rigorous. Each method is presented with both a theoretical background and the practical information that is useful for any data analyst. Empirical examples showcase the real-world applications of the discussed concepts and models, and each chapter concludes with a «Points to Remember» section that contains a brief summary of key ideas. All of the analyses in the book are performed using Proc LCA and Proc LTA, the authors' own software packages that can be run within the SAS® environment. A related Web site houses information on these freely available programs and the book's data sets, encouraging readers to reproduce the analyses and also try their own variations. Latent Class and Latent Transition Analysis is an excellent book for courses on categorical data analysis and latent variable models at the upper-undergraduate and graduate levels. It is also a valuable resource for researchers and practitioners in the social, behavioral, and health sciences who conduct latent class and latent transition analysis in their everyday work.
Johnson Wayne P. Making Sense of Data I. A Practical Guide to Exploratory Data Analysis and Data Mining Johnson Wayne P. Making Sense of Data I. A Practical Guide to Exploratory Data Analysis and Data Mining Новинка

Johnson Wayne P. Making Sense of Data I. A Practical Guide to Exploratory Data Analysis and Data Mining

5977.3 руб.
Praise for the First Edition “…a well-written book on data analysis and data mining that provides an excellent foundation…” —CHOICE “This is a must-read book for learning practical statistics and data analysis…” —Computing Reviews.com A proven go-to guide for data analysis, Making Sense of Data I: A Practical Guide to Exploratory Data Analysis and Data Mining, Second Edition focuses on basic data analysis approaches that are necessary to make timely and accurate decisions in a diverse range of projects. Based on the authors’ practical experience in implementing data analysis and data mining, the new edition provides clear explanations that guide readers from almost every field of study. In order to facilitate the needed steps when handling a data analysis or data mining project, a step-by-step approach aids professionals in carefully analyzing data and implementing results, leading to the development of smarter business decisions. The tools to summarize and interpret data in order to master data analysis are integrated throughout, and the Second Edition also features: Updated exercises for both manual and computer-aided implementation with accompanying worked examples New appendices with coverage on the freely available Traceis™ software, including tutorials using data from a variety of disciplines such as the social sciences, engineering, and finance New topical coverage on multiple linear regression and logistic regression to provide a range of widely used and transparent approaches Additional real-world examples of data preparation to establish a practical background for making decisions from data Making Sense of Data I: A Practical Guide to Exploratory Data Analysis and Data Mining, Second Edition is an excellent reference for researchers and professionals who need to achieve effective decision making from data. The Second Edition is also an ideal textbook for undergraduate and graduate-level courses in data analysis and data mining and is appropriate for cross-disciplinary courses found within computer science and engineering departments.
Nii Attoh-Okine O. Big Data and Differential Privacy. Analysis Strategies for Railway Track Engineering Nii Attoh-Okine O. Big Data and Differential Privacy. Analysis Strategies for Railway Track Engineering Новинка

Nii Attoh-Okine O. Big Data and Differential Privacy. Analysis Strategies for Railway Track Engineering

10123.22 руб.
A comprehensive introduction to the theory and practice of contemporary data science analysis for railway track engineering Featuring a practical introduction to state-of-the-art data analysis for railway track engineering, Big Data and Differential Privacy: Analysis Strategies for Railway Track Engineering addresses common issues with the implementation of big data applications while exploring the limitations, advantages, and disadvantages of more conventional methods. In addition, the book provides a unifying approach to analyzing large volumes of data in railway track engineering using an array of proven methods and software technologies. Dr. Attoh-Okine considers some of today’s most notable applications and implementations and highlights when a particular method or algorithm is most appropriate. Throughout, the book presents numerous real-world examples to illustrate the latest railway engineering big data applications of predictive analytics, such as the Union Pacific Railroad’s use of big data to reduce train derailments, increase the velocity of shipments, and reduce emissions. In addition to providing an overview of the latest software tools used to analyze the large amount of data obtained by railways, Big Data and Differential Privacy: Analysis Strategies for Railway Track Engineering: • Features a unified framework for handling large volumes of data in railway track engineering using predictive analytics, machine learning, and data mining • Explores issues of big data and differential privacy and discusses the various advantages and disadvantages of more conventional data analysis techniques • Implements big data applications while addressing common issues in railway track maintenance • Explores the advantages and pitfalls of data analysis software such as R and Spark, as well as the Apache™ Hadoop® data collection database and its popular implementation MapReduce Big Data and Differential Privacy is a valuable resource for researchers and professionals in transportation science, railway track engineering, design engineering, operations research, and railway planning and management. The book is also appropriate for graduate courses on data analysis and data mining, transportation science, operations research, and infrastructure management. NII ATTOH-OKINE, PhD, PE is Professor in the Department of Civil and Environmental Engineering at the University of Delaware. The author of over 70 journal articles, his main areas of research include big data and data science; computational intelligence; graphical models and belief functions; civil infrastructure systems; image and signal processing; resilience engineering; and railway track analysis. Dr. Attoh-Okine has edited five books in the areas of computational intelligence, infrastructure systems and has served as an Associate Editor of various ASCE and IEEE journals.
Mohamed Daoudi 3D Face Modeling, Analysis and Recognition Mohamed Daoudi 3D Face Modeling, Analysis and Recognition Новинка

Mohamed Daoudi 3D Face Modeling, Analysis and Recognition

9598.21 руб.
3D Face Modeling, Analysis and Recognition presents methodologies for analyzing shapes of facial surfaces, develops computational tools for analyzing 3D face data, and illustrates them using state-of-the-art applications. The methodologies chosen are based on efficient representations, metrics, comparisons, and classifications of features that are especially relevant in the context of 3D measurements of human faces. These frameworks have a long-term utility in face analysis, taking into account the anticipated improvements in data collection, data storage, processing speeds, and application scenarios expected as the discipline develops further. The book covers face acquisition through 3D scanners and 3D face pre-processing, before examining the three main approaches for 3D facial surface analysis and recognition: facial curves; facial surface features; and 3D morphable models. Whilst the focus of these chapters is fundamentals and methodologies, the algorithms provided are tested on facial biometric data, thereby continually showing how the methods can be applied. Key features: • Explores the underlying mathematics and will apply these mathematical techniques to 3D face analysis and recognition • Provides coverage of a wide range of applications including biometrics, forensic applications, facial expression analysis, and model fitting to 2D images • Contains numerous exercises and algorithms throughout the book
Peter Huber J. Data Analysis. What Can Be Learned From the Past 50 Years Peter Huber J. Data Analysis. What Can Be Learned From the Past 50 Years Новинка

Peter Huber J. Data Analysis. What Can Be Learned From the Past 50 Years

10115.42 руб.
This book explores the many provocative questions concerning the fundamentals of data analysis. It is based on the time-tested experience of one of the gurus of the subject matter. Why should one study data analysis? How should it be taught? What techniques work best, and for whom? How valid are the results? How much data should be tested? Which machine languages should be used, if used at all? Emphasis on apprenticeship (through hands-on case studies) and anecdotes (through real-life applications) are the tools that Peter J. Huber uses in this volume. Concern with specific statistical techniques is not of immediate value; rather, questions of strategy – when to use which technique – are employed. Central to the discussion is an understanding of the significance of massive (or robust) data sets, the implementation of languages, and the use of models. Each is sprinkled with an ample number of examples and case studies. Personal practices, various pitfalls, and existing controversies are presented when applicable. The book serves as an excellent philosophical and historical companion to any present-day text in data analysis, robust statistics, data mining, statistical learning, or computational statistics.
Sana Salous Radio Propagation Measurement and Channel Modelling Sana Salous Radio Propagation Measurement and Channel Modelling Новинка

Sana Salous Radio Propagation Measurement and Channel Modelling

10192.06 руб.
While there are numerous books describing modern wireless communication systems that contain overviews of radio propagation and radio channel modelling, there are none that contain detailed information on the design, implementation and calibration of radio channel measurement equipment, the planning of experiments and the in depth analysis of measured data. The book would begin with an explanation of the fundamentals of radio wave propagation and progress through a series of topics, including the measurement of radio channel characteristics, radio channel sounders, measurement strategies, data analysis techniques and radio channel modelling. Application of results for the prediction of achievable digital link performance would be discussed with examples pertinent to single carrier, multi-carrier and spread spectrum radio links. This work would address specifics of communications in various different frequency bands for both long range and short range fixed and mobile radio links.
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.
Ion Mandoiu Computational Methods for Next Generation Sequencing Data Analysis Ion Mandoiu Computational Methods for Next Generation Sequencing Data Analysis Новинка

Ion Mandoiu Computational Methods for Next Generation Sequencing Data Analysis

8997.79 руб.
Introduces readers to core algorithmic techniques for next-generation sequencing (NGS) data analysis and discusses a wide range of computational techniques and applications This book provides an in-depth survey of some of the recent developments in NGS and discusses mathematical and computational challenges in various application areas of NGS technologies. The 18 chapters featured in this book have been authored by bioinformatics experts and represent the latest work in leading labs actively contributing to the fast-growing field of NGS. The book is divided into four parts: Part I focuses on computing and experimental infrastructure for NGS analysis, including chapters on cloud computing, modular pipelines for metabolic pathway reconstruction, pooling strategies for massive viral sequencing, and high-fidelity sequencing protocols. Part II concentrates on analysis of DNA sequencing data, covering the classic scaffolding problem, detection of genomic variants, including insertions and deletions, and analysis of DNA methylation sequencing data. Part III is devoted to analysis of RNA-seq data. This part discusses algorithms and compares software tools for transcriptome assembly along with methods for detection of alternative splicing and tools for transcriptome quantification and differential expression analysis. Part IV explores computational tools for NGS applications in microbiomics, including a discussion on error correction of NGS reads from viral populations, methods for viral quasispecies reconstruction, and a survey of state-of-the-art methods and future trends in microbiome analysis. Computational Methods for Next Generation Sequencing Data Analysis: Reviews computational techniques such as new combinatorial optimization methods, data structures, high performance computing, machine learning, and inference algorithms Discusses the mathematical and computational challenges in NGS technologies Covers NGS error correction, de novo genome transcriptome assembly, variant detection from NGS reads, and more This text is a reference for biomedical professionals interested in expanding their knowledge of computational techniques for NGS data analysis. The book is also useful for graduate and post-graduate students in bioinformatics.
Trisha Dunning Care of People with Diabetes. A Manual of Nursing Practice Trisha Dunning Care of People with Diabetes. A Manual of Nursing Practice Новинка

Trisha Dunning Care of People with Diabetes. A Manual of Nursing Practice

2139.84 руб.
‘This remarkably comprehensive book reflects the depth of knowledge and experience of its author and will assist nurses in the process of diabetes management. I wholeheartedly recommend this text to all health professionals whether working directly in, or on, the fringe of diabetes. ‘ From the foreword by Marg McGill, Chair, International Diabetes Federation Consultative Section on Diabetes Education Care of People with Diabetes is an essential guide to the care and management of people with diabetes mellitus, with particular emphasis on the acute care setting. It is written by an experienced clinical nurse specialist with extensive knowledge of evidence-based diabetes care. The book serves as an essential companion to clinical practice for nurses and health professionals. This third edition of Care of People with Diabetes has been extensively revised, and includes new information on smoking cessation, diabetes and driving, coeliac disease and Polycystic Ovarian Syndrome. Key features: Fully revised new edition of a successful text Provides the evidence for best practice Includes protocols for consistent care and improvement of patient outcomes Each chapter includes lists of key points, boxes highlighting key information, further reading, patient information, and patient care sheets.
DeWayne Derryberry R. Basic Data Analysis for Time Series with R DeWayne Derryberry R. Basic Data Analysis for Time Series with R Новинка

DeWayne Derryberry R. Basic Data Analysis for Time Series with R

8922.38 руб.
Written at a readily accessible level, Basic Data Analysis for Time Series with R emphasizes the mathematical importance of collaborative analysis of data used to collect increments of time or space. Balancing a theoretical and practical approach to analyzing data within the context of serial correlation, the book presents a coherent and systematic regression-based approach to model selection. The book illustrates these principles of model selection and model building through the use of information criteria, cross validation, hypothesis tests, and confidence intervals. Focusing on frequency- and time-domain and trigonometric regression as the primary themes, the book also includes modern topical coverage on Fourier series and Akaike's Information Criterion (AIC). In addition, Basic Data Analysis for Time Series with R also features: Real-world examples to provide readers with practical hands-on experience Multiple R software subroutines employed with graphical displays Numerous exercise sets intended to support readers understanding of the core concepts Specific chapters devoted to the analysis of the Wolf sunspot number data and the Vostok ice core data sets
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.
Michel Geradin Mechanical Vibrations. Theory and Application to Structural Dynamics Michel Geradin Mechanical Vibrations. Theory and Application to Structural Dynamics Новинка

Michel Geradin Mechanical Vibrations. Theory and Application to Structural Dynamics

10047.81 руб.
Mechanical Vibrations: Theory and Application to Structural Dynamics, Third Edition is a comprehensively updated new edition of the popular textbook. It presents the theory of vibrations in the context of structural analysis and covers applications in mechanical and aerospace engineering. Key features include: A systematic approach to dynamic reduction and substructuring, based on duality between mechanical and admittance concepts An introduction to experimental modal analysis and identification methods An improved, more physical presentation of wave propagation phenomena A comprehensive presentation of current practice for solving large eigenproblems, focusing on the efficient linear solution of large, sparse and possibly singular systems A deeply revised description of time integration schemes, providing framework for the rigorous accuracy/stability analysis of now widely used algorithms such as HHT and Generalized-α Solved exercises and end of chapter homework problems A companion website hosting supplementary material
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.
Giudici Paolo Applied Data Mining for Business and Industry Giudici Paolo Applied Data Mining for Business and Industry Новинка

Giudici Paolo Applied Data Mining for Business and Industry

14176.92 руб.
The increasing availability of data in our current, information overloaded society has led to the need for valid tools for its modelling and analysis. Data mining and applied statistical methods are the appropriate tools to extract knowledge from such data. This book provides an accessible introduction to data mining methods in a consistent and application oriented statistical framework, using case studies drawn from real industry projects and highlighting the use of data mining methods in a variety of business applications. Introduces data mining methods and applications. Covers classical and Bayesian multivariate statistical methodology as well as machine learning and computational data mining methods. Includes many recent developments such as association and sequence rules, graphical Markov models, lifetime value modelling, credit risk, operational risk and web mining. Features detailed case studies based on applied projects within industry. Incorporates discussion of data mining software, with case studies analysed using R. Is accessible to anyone with a basic knowledge of statistics or data analysis. Includes an extensive bibliography and pointers to further reading within the text. Applied Data Mining for Business and Industry, 2nd edition is aimed at advanced undergraduate and graduate students of data mining, applied statistics, database management, computer science and economics. The case studies will provide guidance to professionals working in industry on projects involving large volumes of data, such as customer relationship management, web design, risk management, marketing, economics and finance.
Terje Aven Risk Analysis Terje Aven Risk Analysis Новинка

Terje Aven Risk Analysis

5634.29 руб.
Risk Analysis, Second Edition Terje Aven, University of Stavanger, Norway A practical guide to the varied challenges presented in the ever-growing field of risk analysis. Risk Analysis presents an accessible and concise guide to performing risk analysis, in a wide variety of field, with minimal prior knowledge required. Forming an ideal companion volume to Aven's previous Wiley text Foundations of Risk Analysis, it provides clear recommendations and guidance in the planning, execution anduse of risk analysis. This new edition presents recent developments related to risk conceptualization, focusing on related issues on risk assessment and their application. New examples are also featured to clarify the reader's understanding in the application of risk analysis and the risk analysis process. Key features: Fully updated to include recent developments related to risk conceptualization and related issues on risk assessments and their applications. Emphasizes the decision making context of risk analysis rather than just computing probabilities Demonstrates how to carry out predictive risk analysis using a variety of case studies and examples. Written by an experienced expert in the field, in a style suitable for both industrial and academic audiences. This book is ideal for advanced undergraduates, graduates, analysts and researchers from statistics, engineering, finance, medicine and physical sciences. Managers facing decision making problems involving risk and uncertainty will also benefit from this book.
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.
I. Gusti Ngurah Agung Panel Data Analysis using EViews I. Gusti Ngurah Agung Panel Data Analysis using EViews Новинка

I. Gusti Ngurah Agung Panel Data Analysis using EViews

11111.64 руб.
A comprehensive and accessible guide to panel data analysis using EViews software This book explores the use of EViews software in creating panel data analysis using appropriate empirical models and real datasets. Guidance is given on developing alternative descriptive statistical summaries for evaluation and providing policy analysis based on pool panel data. Various alternative models based on panel data are explored, including univariate general linear models, fixed effect models and causal models, and guidance on the advantages and disadvantages of each one is given. Panel Data Analysis using EViews: Provides step-by-step guidance on how to apply EViews software to panel data analysis using appropriate empirical models and real datasets. Examines a variety of panel data models along with the author’s own empirical findings, demonstrating the advantages and limitations of each model. Presents growth models, time-related effects models, and polynomial models, in addition to the models which are commonly applied for panel data. Includes more than 250 examples divided into three groups of models (stacked, unstacked, and structured panel data), together with notes and comments. Provides guidance on which models not to use in a given scenario, along with advice on viable alternatives. Explores recent new developments in panel data analysis An essential tool for advanced undergraduate or graduate students and applied researchers in finance, econometrics and population studies. Statisticians and data analysts involved with data collected over long time periods will also find this book a useful resource.
F. Carlevaro Econometric Modeling and Analysis of Residential Water Demand Based on Unbalanced Panel Data F. Carlevaro Econometric Modeling and Analysis of Residential Water Demand Based on Unbalanced Panel Data Новинка

F. Carlevaro Econometric Modeling and Analysis of Residential Water Demand Based on Unbalanced Panel Data

79.9 руб.
This paper develops an econometric methodology devised to analyze a sample of time unbalanced panel data on residential water consumption in the French island La Reunion with the purpose to bring out the main determinants of household water consumption and estimate the importance of water consumption by uses. For this purpose, we specify a daily panel econometric model and derive, by performing a time aggregation, a general linear regression model accounting for water consumption data recorded on periods of any calendar date and time length. To estimate efficiently the parameters of this model we develop a feasible two step generalized least square method. Using the principle of best linear unbiaised prediction, we finally develop an approach allowing to consistenly break down the volume of water consumption recorded on household water bills by uses, namely by enforcing this estimated decomposition to add up to the observed total. The application of this methodology to a sample of 437 unbalanced panel observations shows the scope of this approach for the empirical analysis of actual data.
Thomas Lumley Complex Surveys. A Guide to Analysis Using R Thomas Lumley Complex Surveys. A Guide to Analysis Using R Новинка

Thomas Lumley Complex Surveys. A Guide to Analysis Using R

6893.05 руб.
A complete guide to carrying out complex survey analysis using R As survey analysis continues to serve as a core component of sociological research, researchers are increasingly relying upon data gathered from complex surveys to carry out traditional analyses. Complex Surveys is a practical guide to the analysis of this kind of data using R, the freely available and downloadable statistical programming language. As creator of the specific survey package for R, the author provides the ultimate presentation of how to successfully use the software for analyzing data from complex surveys while also utilizing the most current data from health and social sciences studies to demonstrate the application of survey research methods in these fields. The book begins with coverage of basic tools and topics within survey analysis such as simple and stratified sampling, cluster sampling, linear regression, and categorical data regression. Subsequent chapters delve into more technical aspects of complex survey analysis, including post-stratification, two-phase sampling, missing data, and causal inference. Throughout the book, an emphasis is placed on graphics, regression modeling, and two-phase designs. In addition, the author supplies a unique discussion of epidemiological two-phase designs as well as probability-weighting for causal inference. All of the book's examples and figures are generated using R, and a related Web site provides the R code that allows readers to reproduce the presented content. Each chapter concludes with exercises that vary in level of complexity, and detailed appendices outline additional mathematical and computational descriptions to assist readers with comparing results from various software systems. Complex Surveys is an excellent book for courses on sampling and complex surveys at the upper-undergraduate and graduate levels. It is also a practical reference guide for applied statisticians and practitioners in the social and health sciences who use statistics in their everyday work.
Otto Wildi Data Analysis in Vegetation Ecology Otto Wildi Data Analysis in Vegetation Ecology Новинка

Otto Wildi Data Analysis in Vegetation Ecology

11490.97 руб.
Evolving from years of teaching experience by one of the top experts in vegetation ecology, Data Analysis in Vegetation Ecology aims to explain the background and basics of mathematical (mainly multivariate) analysis of vegetation data. The book lays out the basic operations involved in the analysis, the underlying hypotheses, aims and points of views. It conveys the message that each step in the calculations has a specific, straightforward meaning and that patterns and processes known by ecologists often find their counterpart in mathematical operations and functions. The first chapters introduce the elementary concepts and operations and relate them to real-world phenomena and problems. Later chapters concentrate on combinations of methods to reveal surprising features in data sets. Showing how to find patterns in time series, how to generate simple dynamic models, how to reveal spatial patterns and related occurrence probability maps.
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.
Tisdell Elizabeth J. Qualitative Research. A Guide to Design and Implementation Tisdell Elizabeth J. Qualitative Research. A Guide to Design and Implementation Новинка

Tisdell Elizabeth J. Qualitative Research. A Guide to Design and Implementation

3831.6 руб.
The bestselling guide to qualitative research, updated and expanded Qualitative Research is the essential guide to understanding, designing, conducting, and presenting a qualitative research study. This fourth edition features new material covering mixed methods, action research, arts-based research, online data sources, and the latest in data analysis, including data analysis software packages as well as narrative and poetic analysis strategies. A new section offers multiple ways of presenting qualitative research findings. The reader-friendly, jargon-free style makes this book accessible to both novice and experienced researchers, emphasizing the role of a theoretical framework in designing a study while providing practical guidance. Qualitative research reaches beyond the what, where, and when of quantitative analysis to investigate the why and how behind human behavior and the reasons that govern such behavior, but this presents a number of significant challenges. This guide is an invaluable reference for students and practitioners alike, providing the deep understanding that this sometimes difficult area of research requires to produce accurate results. The book contains a step-by-step guide to analyzing qualitative data and an addendum for graduate students with a template for a thesis, dissertation, or grant application. Build a strong foundation in qualitative research theory and application Design and implement effective qualitative research studies Communicate findings more successfully with clear presentation Explore data sources, data analysis tools, and the different types of research
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.
Mun Eun-Young Log-Linear Modeling. Concepts, Interpretation, and Application Mun Eun-Young Log-Linear Modeling. Concepts, Interpretation, and Application Новинка

Mun Eun-Young Log-Linear Modeling. Concepts, Interpretation, and Application

10115.42 руб.
An easily accessible introduction to log-linear modeling for non-statisticians Highlighting advances that have lent to the topic's distinct, coherent methodology over the past decade, Log-Linear Modeling: Concepts, Interpretation, and Application provides an essential, introductory treatment of the subject, featuring many new and advanced log-linear methods, models, and applications. The book begins with basic coverage of categorical data, and goes on to describe the basics of hierarchical log-linear models as well as decomposing effects in cross-classifications and goodness-of-fit tests. Additional topics include: The generalized linear model (GLM) along with popular methods of coding such as effect coding and dummy coding Parameter interpretation and how to ensure that the parameters reflect the hypotheses being studied Symmetry, rater agreement, homogeneity of association, logistic regression, and reduced designs models Throughout the book, real-world data illustrate the application of models and understanding of the related results. In addition, each chapter utilizes R, SYSTAT®, and §¤EM software, providing readers with an understanding of these programs in the context of hierarchical log-linear modeling. Log-Linear Modeling is an excellent book for courses on categorical data analysis at the upper-undergraduate and graduate levels. It also serves as an excellent reference for applied researchers in virtually any area of study, from medicine and statistics to the social sciences, who analyze empirical data in their everyday work.
Luca Massaron Python for Data Science For Dummies Luca Massaron Python for Data Science For Dummies Новинка

Luca Massaron Python for Data Science For Dummies

1913.35 руб.
Unleash the power of Python for your data analysis projects with For Dummies! Python is the preferred programming language for data scientists and combines the best features of Matlab, Mathematica, and R into libraries specific to data analysis and visualization. Python for Data Science For Dummies shows you how to take advantage of Python programming to acquire, organize, process, and analyze large amounts of information and use basic statistics concepts to identify trends and patterns. You’ll get familiar with the Python development environment, manipulate data, design compelling visualizations, and solve scientific computing challenges as you work your way through this user-friendly guide. Covers the fundamentals of Python data analysis programming and statistics to help you build a solid foundation in data science concepts like probability, random distributions, hypothesis testing, and regression models Explains objects, functions, modules, and libraries and their role in data analysis Walks you through some of the most widely-used libraries, including NumPy, SciPy, BeautifulSoup, Pandas, and MatPlobLib Whether you’re new to data analysis or just new to Python, Python for Data Science For Dummies is your practical guide to getting a grip on data overload and doing interesting things with the oodles of information you uncover.
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.
Jean-Christophe Plantin Participatory Mapping. New Data, New Cartography Jean-Christophe Plantin Participatory Mapping. New Data, New Cartography Новинка

Jean-Christophe Plantin Participatory Mapping. New Data, New Cartography

6973.85 руб.
This book is intended for applications of online digital mapping, called mashups (or composite application), and to analyze the mapping practices in online socio-technical controversies. The hypothesis put forward is that the ability to create an online map accompanies the formation of online audience and provides support for a position in a debate on the Web. The first part provides a study of the map: – a combination of map and statistical reason – crosses between map theories and CIS theories – recent developments in scanning the map, from Geographic Information Systems (GIS) to Web map. The second part is based on a corpus of twenty «mashup» maps, and offers a techno-semiotic analysis highlighting the «thickness of the mediation» they are in a process of communication on the Web. Map as a device to «make do» is thus replaced through these stages of creation, ranging from digital data in their viewing, before describing the construction of the map as a tool for visual evidence in public debates, and ending with an analysis of the delegation action against Internet users. The third section provides an analysis of these mapping practices in the case study of the controversy over nuclear radiation following the accident at the Fukushima plant on March 11, 2011. Techno-semiotic method applied to this corpus of radiation map is supplemented by an analysis of web graphs, derived from «digital methods» and graph theory, accompanying the analysis of the previous steps maps (creating Geiger data or retrieving files online), but also their movement, once maps are made.
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.
Daniel Larose T. Data Mining and Predictive Analytics Daniel Larose T. Data Mining and Predictive Analytics Новинка

Daniel Larose T. Data Mining and Predictive Analytics

10497.42 руб.
Learn methods of data analysis and their application to real-world data sets This updated second edition serves as an introduction to data mining methods and models, including association rules, clustering, neural networks, logistic regression, and multivariate analysis. The authors apply a unified “white box” approach to data mining methods and models. This approach is designed to walk readers through the operations and nuances of the various methods, using small data sets, so readers can gain an insight into the inner workings of the method under review. Chapters provide readers with hands-on analysis problems, representing an opportunity for readers to apply their newly-acquired data mining expertise to solving real problems using large, real-world data sets. Data Mining and Predictive Analytics, Second Edition: Offers comprehensive coverage of association rules, clustering, neural networks, logistic regression, multivariate analysis, and R statistical programming language Features over 750 chapter exercises, allowing readers to assess their understanding of the new material Provides a detailed case study that brings together the lessons learned in the book Includes access to the companion website, www.dataminingconsultant.com, with exclusive password-protected instructor content Data Mining and Predictive Analytics, Second Edition will appeal to computer science and statistic students, as well as students in MBA programs, and chief executives.
Ian Blumer Diabetes For Canadians For Dummies Ian Blumer Diabetes For Canadians For Dummies Новинка

Ian Blumer Diabetes For Canadians For Dummies

1910.8 руб.
Get the facts on treating diabetes successfully and living a full and active life As Canada's ultimate diabetes resource, this helpful guide returns with a new edition—thoroughly revised and updated with the latest guidelines from the Canadian Diabetes Association, along with new medical findings. Offering you reassuring guidance for putting together a state-of-the-art diabetes treatment program, this friendly-yet-informative book walks you through all the advances in monitoring glucose, the latest medications, ways to juggle diabetes with daily commitments, and how to develop a diet and exercise plan to stay healthy. Packed with helpful advice, Diabetes For Canadians For Dummies, Third Edition explores the newest data about the diagnosis and treatment of people with diabetes, including children and women during pregnancy. The author duo puts their years of diabetes expertise to use by deciphering information from recent studies that provide new insights into how diabetes affects the body and walks you through the latest drugs used to treat this manageable disease. Teaches you how to identify the symptoms that require urgent attention and how to subsequently treat the problem Reassures you of what to do during pregnancy to help ensure a healthy baby Shares advice for finding the right health care providers, from your family physician to your diabetes nurse educator to your dietician, and more Addresses concerns regarding driving with hypoglycemia Discusses the latest connection between the brain and diabetes and looks at new nutritional data from the latest version of Canada's Food Guide Diabetes For Canadians For Dummies, Third Edition features new nutritional data, facts on prediabetes, and advice for prevention tactics, all of which provide you with an arsenal of information that will help you manage your diabetes confidently and wisely.
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.
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.
Allen John R. Basin Analysis. Principles and Applications Allen John R. Basin Analysis. Principles and Applications Новинка

Allen John R. Basin Analysis. Principles and Applications

9192.01 руб.
Basin Analysis is an up-to-date overview of the essential processes of the formation and evolution of sedimentary basins, and their implications for the development of hydrocarbon resources. The new edition features: A consideration of the fundamental physical state of the lithosphere. A discussion on the major types of lithospheric deformation relevant to basin development – stretching and flexure. A new chapter on the effects of mantle dynamics. Radically revised chapters on the basin-fill. A new chapter on the erosional engine for sediment delivery to basins, reflecting the massive and exciting advances in this area in the last decade. Expansion of the techniques used in approaching problems in basin analysis. Updated chapters on subsidence analysis and measurements of thermal maturity of organic and non-organic components of the basin-fill. New material on thermochronological and exposure dating tools. Inclusion of the important petroleum system concept in the updated section on the application to the petroleum play. Visit: www.blackwellpublishing.com/allen for practical exercises related to problems in Basin Analysis 2e. To run the programs you will need a copy of Matlab 6 or 7. An Instructor manual CD-ROM for this title is available. Please contact our Higher Education team at [email protected] for more information.
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.
I. Gusti Ngurah Agung Cross Section and Experimental Data Analysis Using EViews I. Gusti Ngurah Agung Cross Section and Experimental Data Analysis Using EViews Новинка

I. Gusti Ngurah Agung Cross Section and Experimental Data Analysis Using EViews

11111.64 руб.
A practical guide to selecting and applying the most appropriate model for analysis of cross section data using EViews. «This book is a reflection of the vast experience and knowledge of the author. It is a useful reference for students and practitioners dealing with cross sectional data analysis … The strength of the book lies in its wealth of material and well structured guidelines …» Prof. Yohanes Eko Riyanto, Nanyang Technological University, Singapore «This is superb and brilliant. Prof. Agung has skilfully transformed his best experiences into new knowledge … creating a new way of understanding data analysis.» Dr. I Putu Gede Ary Suta, The Ary Suta Center, Jakarta Basic theoretical concepts of statistics as well as sampling methods are often misinterpreted by students and less experienced researchers. This book addresses this issue by providing a hands-on practical guide to conducting data analysis using EViews combined with a variety of illustrative models (and their extensions). Models having numerically dependent variables based on a cross-section data set (such as univariate, multivariate and nonlinear models as well as non-parametric regressions) are concentrated on. It is shown that a wide variety of hypotheses can easily be tested using EViews. Cross Section and Experimental Data Analysis Using EViews: Provides step-by-step directions on how to apply EViews to cross section data analysis – from multivariate analysis and nonlinear models to non-parametric regression Presents a method to test for all possible hypotheses based on each model Proposes a new method for data analysis based on a multifactorial design model Demonstrates that statistical summaries in the form of tabulations are invaluable inputs for strategic decision making Contains 200 examples with special notes and comments based on the author’s own empirical findings as well as over 400 illustrative outputs of regressions from EViews Techniques are illustrated through practical examples from real situations Comes with supplementary material, including work-files containing selected equation and system specifications that have been applied in the book This user-friendly introduction to EViews is ideal for Advanced undergraduate and graduate students taking finance, econometrics, population, or public policy courses, as well as applied policy researchers.
Martin Kent Vegetation Description and Data Analysis. A Practical Approach Martin Kent Vegetation Description and Data Analysis. A Practical Approach Новинка

Martin Kent Vegetation Description and Data Analysis. A Practical Approach

2139.84 руб.
Vegetation Description and Data Analysis: A Practical Approach, Second Edition is a fully revised and up-dated edition of this key text. The book takes account of recent advances in the field whilst retaining the original reader-friendly approach to the coverage of vegetation description and multivariate analysis in the context of vegetation data and plant ecology. Since the publication of the hugely popular first edition there have been significant developments in computer hardware and software, new key journals have been established in the field and scope and application of vegetation description and analysis has become a truly global field. This new edition includes full coverage of new developments and technologies. This contemporary and comprehensive edition of this well-known and respected textbook will prove invaluable to undergraduate and graduate students in biological sciences, environmental science, geography, botany, agriculture, forestry and biological conservation. Fully international approach Includes illustrative case studies throughout Now with new material on: the nature of plant communities; transitional areas between plant communities; induction and deduction of plant ecology; diversity indices and dominance diversity curves; multivariate analysis in ecology. Accessible, reader-friendly style Now with new and improved illustrations
Roger Mazze Staged Diabetes Management Roger Mazze Staged Diabetes Management Новинка

Roger Mazze Staged Diabetes Management

13193.62 руб.
This new edition of the successful Staged Diabetes Management will again address the prominent issues of primary care diabetes management based on the International Diabetes Center’s “Staged Diabetes Management” program, which it advocates as part of its mission statement. This systematic treatment program consists of practical solutions to the detection and treatment of diabetes, its complications, and such areas as metabolic syndrome, pre-diabete,s and diabetes in children using evidence-based medicine. The text reviews the fundamental basis of diabetes management and then addresses treatment of each type of diabetes and the major micro- and macrovascular complications.
Dehmer Matthias Statistical and Machine Learning Approaches for Network Analysis Dehmer Matthias Statistical and Machine Learning Approaches for Network Analysis Новинка

Dehmer Matthias Statistical and Machine Learning Approaches for Network Analysis

9732.26 руб.
Explore the multidisciplinary nature of complex networks through machine learning techniques Statistical and Machine Learning Approaches for Network Analysis provides an accessible framework for structurally analyzing graphs by bringing together known and novel approaches on graph classes and graph measures for classification. By providing different approaches based on experimental data, the book uniquely sets itself apart from the current literature by exploring the application of machine learning techniques to various types of complex networks. Comprised of chapters written by internationally renowned researchers in the field of interdisciplinary network theory, the book presents current and classical methods to analyze networks statistically. Methods from machine learning, data mining, and information theory are strongly emphasized throughout. Real data sets are used to showcase the discussed methods and topics, which include: A survey of computational approaches to reconstruct and partition biological networks An introduction to complex networks—measures, statistical properties, and models Modeling for evolving biological networks The structure of an evolving random bipartite graph Density-based enumeration in structured data Hyponym extraction employing a weighted graph kernel Statistical and Machine Learning Approaches for Network Analysis is an excellent supplemental text for graduate-level, cross-disciplinary courses in applied discrete mathematics, bioinformatics, pattern recognition, and computer science. The book is also a valuable reference for researchers and practitioners in the fields of applied discrete mathematics, machine learning, data mining, and biostatistics.
Jack Hardisty The Analysis of Tidal Stream Power Jack Hardisty The Analysis of Tidal Stream Power Новинка

Jack Hardisty The Analysis of Tidal Stream Power

13483.4 руб.
This text integrates a wide range of research and tidal resource theory and data to present a detailed analysis of the physics and oceanography of tidal stream power devices together with a world wide resource analysis. Clearly structured throughout the book is divided into two distinct parts. Part One provides the theoretical background to the subject and deals with the historical development of the harmonic method for the synthesis of tidal currents; the principles of fluid and tidal flow and the principles of device ducts, turbines and electrical systems. A review and analysis of more than forty tidal stream power proposals is also discussed. Part Two provides a comprehensive overview of current practice. The economic modelling of tidal stream power installations is covered with more than three hundred current meter records from around the world used to analyse the potential and cost of tidal stream power on a global basis. Hallmark Features: reviews the tidal resources around the world complete analysis of tidal stream power systems includes historical information on tidal science and biographical information on major figures concentrates on engineering physical geography rather than engineering specifics includes a website with a wide range of computer models, data and simulations

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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 application of longitudinal data analysis on fbs of adult diabetes лучших цены всего мира
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