Statistical Techniques For Data Analysis
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Statistical Techniques For Data Analysis
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Author : John K. Taylor
language : en
Publisher: CRC Press
Release Date : 2004-01-14
Statistical Techniques For Data Analysis written by John K. Taylor and has been published by CRC Press this book supported file pdf, txt, epub, kindle and other format this book has been release on 2004-01-14 with Mathematics categories.
Since the first edition of this book appeared, computers have come to the aid of modern experimenters and data analysts, bringing with them data analysis techniques that were once beyond the calculational reach of even professional statisticians. Today, scientists in every field have access to the techniques and technology they need to analyze stat
Advanced Statistical Methods In Data Science
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Author : Ding-Geng Chen
language : en
Publisher: Springer
Release Date : 2016-11-30
Advanced Statistical Methods In Data Science written by Ding-Geng Chen and has been published by Springer this book supported file pdf, txt, epub, kindle and other format this book has been release on 2016-11-30 with Mathematics categories.
This book gathers invited presentations from the 2nd Symposium of the ICSA- CANADA Chapter held at the University of Calgary from August 4-6, 2015. The aim of this Symposium was to promote advanced statistical methods in big-data sciences and to allow researchers to exchange ideas on statistics and data science and to embraces the challenges and opportunities of statistics and data science in the modern world. It addresses diverse themes in advanced statistical analysis in big-data sciences, including methods for administrative data analysis, survival data analysis, missing data analysis, high-dimensional and genetic data analysis, longitudinal and functional data analysis, the design and analysis of studies with response-dependent and multi-phase designs, time series and robust statistics, statistical inference based on likelihood, empirical likelihood and estimating functions. The editorial group selected 14 high-quality presentations from this successful symposium and invited the presenters to prepare a full chapter for this book in order to disseminate the findings and promote further research collaborations in this area. This timely book offers new methods that impact advanced statistical model development in big-data sciences.
Statistical Data Analysis
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Author : Milan Meloun
language : en
Publisher: Woodhead Publishing Limited
Release Date : 2011
Statistical Data Analysis written by Milan Meloun and has been published by Woodhead Publishing Limited this book supported file pdf, txt, epub, kindle and other format this book has been release on 2011 with Chemical engineering categories.
Over the past decade, computer supported data analysis by statistical methods has been one of the fastest growth areas in chemometrics, biometrics and other related branches of natural, technical and social sciences. This has been strongly supported by the development of exploratory data analysis, testing assumptions about data, model and statistical methods and computer intensive techniques. This book presents a combination of individual topics with solved problems and a collection of experimental tasks. Methods suitable for extreme or small and large datasets are described. Presents a combination of individual topics in one complete volume featuring statistical analysis of univariate and multivariate data Interspersed throughout with solved problems and experimental tasks suitable for extreme or small and large datasets Features the interpretation of results based on the comprehensive information about data behaviour and validity of used assumptions
Statistical Methods For Astronomical Data Analysis
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Author : Asis Kumar Chattopadhyay
language : en
Publisher: Springer
Release Date : 2014-10-01
Statistical Methods For Astronomical Data Analysis written by Asis Kumar Chattopadhyay and has been published by Springer this book supported file pdf, txt, epub, kindle and other format this book has been release on 2014-10-01 with Mathematics categories.
This book introduces “Astrostatistics” as a subject in its own right with rewarding examples, including work by the authors with galaxy and Gamma Ray Burst data to engage the reader. This includes a comprehensive blending of Astrophysics and Statistics. The first chapter’s coverage of preliminary concepts and terminologies for astronomical phenomenon will appeal to both Statistics and Astrophysics readers as helpful context. Statistics concepts covered in the book provide a methodological framework. A unique feature is the inclusion of different possible sources of astronomical data, as well as software packages for converting the raw data into appropriate forms for data analysis. Readers can then use the appropriate statistical packages for their particular data analysis needs. The ideas of statistical inference discussed in the book help readers determine how to apply statistical tests. The authors cover different applications of statistical techniques already developed or specifically introduced for astronomical problems, including regression techniques, along with their usefulness for data set problems related to size and dimension. Analysis of missing data is an important part of the book because of its significance for work with astronomical data. Both existing and new techniques related to dimension reduction and clustering are illustrated through examples. There is detailed coverage of applications useful for classification, discrimination, data mining and time series analysis. Later chapters explain simulation techniques useful for the development of physical models where it is difficult or impossible to collect data. Finally, coverage of the many R programs for techniques discussed makes this book a fantastic practical reference. Readers may apply what they learn directly to their data sets in addition to the data sets included by the authors.
Quantitative Medical Data Analysis Using Mathematical Tools And Statistical Techniques
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Author : Don Hong
language : en
Publisher: World Scientific
Release Date : 2007-07-10
Quantitative Medical Data Analysis Using Mathematical Tools And Statistical Techniques written by Don Hong and has been published by World Scientific this book supported file pdf, txt, epub, kindle and other format this book has been release on 2007-07-10 with Medical categories.
Quantitative biomedical data analysis is a fast-growing interdisciplinary area of applied and computational mathematics, statistics, computer science, and biomedical science, leading to new fields such as bioinformatics, biomathematics, and biostatistics. In addition to traditional statistical techniques and mathematical models using differential equations, new developments with a very broad spectrum of applications, such as wavelets, spline functions, curve and surface subdivisions, sampling, and learning theory, have found their mathematical home in biomedical data analysis.This book gives a new and integrated introduction to quantitative medical data analysis from the viewpoint of biomathematicians, biostatisticians, and bioinformaticians. It offers a definitive resource to bridge the disciplines of mathematics, statistics, and biomedical sciences. Topics include mathematical models for cancer invasion and clinical sciences, data mining techniques and subset selection in data analysis, survival data analysis and survival models for cancer patients, statistical analysis and neural network techniques for genomic and proteomic data analysis, wavelet and spline applications for mass spectrometry data preprocessing and statistical computing.
Statistical Methods Of Analysis
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Author : Chin Long Chiang
language : en
Publisher: World Scientific Publishing Company
Release Date : 2003-10-01
Statistical Methods Of Analysis written by Chin Long Chiang and has been published by World Scientific Publishing Company this book supported file pdf, txt, epub, kindle and other format this book has been release on 2003-10-01 with Mathematics categories.
This textbook systematically presents fundamental methods of statistical analysis: from probability and statistical distributions, through basic concepts of statistical inference, to a collection of methods of analysis useful for scientific research. It is rich in tables, diagrams, and examples, in addition to theoretical justification of the methods of analysis introduced. Each chapter has a section entitled “Exercises and Problems” to accompany the text. There are altogether about 300 exercises and problems, answers to the selected problems are given. A section entitled “Proof of the Results in This Chapter” in each chapter provides interested readers with material for further study.
Statistical Methods
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Author : Donna L. Mohr
language : en
Publisher: Academic Press
Release Date : 2010-08-17
Statistical Methods written by Donna L. Mohr and has been published by Academic Press this book supported file pdf, txt, epub, kindle and other format this book has been release on 2010-08-17 with Mathematics categories.
Statistical Methods, Third Edition, provides students with a working introduction to statistical methods offering a wide range of applications that emphasize the quantitative skills useful across many academic disciplines. This text takes a classic approach that emphasizes concepts and techniques for working out problems and intepreting results. The book includes research projects, real-world case studies, numerous examples, and data exercises organized by level of difficulty. Students are required to be familiar with algebra. This updated edition includes new exercises applying different techniques and methods; new examples and datasets using current real-world data; new text organization to create a more natural connection between regression and the Analysis of the Variance; new material on generalized linear models; new expansion of nonparametric techniques; new student research projects; and new case studies for gathering, summarizing, and analyzing data. - Integrates the classical conceptual approach with modern day computerized data manipulation and computer applications - Accessibile to students who may not have a background in probability or calculus - Offers reader-friendly exposition, without sacrificing statistical rigor - Includes many new data sets in various applied fields such as Psychology, Education, Biostatistics, Agriculture, Economics
Statistical Analysis And Data Display
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Author : Richard M. Heiberger
language : en
Publisher: Springer Science & Business Media
Release Date : 2013-06-29
Statistical Analysis And Data Display written by Richard M. Heiberger and has been published by Springer Science & Business Media this book supported file pdf, txt, epub, kindle and other format this book has been release on 2013-06-29 with Mathematics categories.
1 Audience Students seeking master's degrees in applied statistics in the late 1960s and 1970s typically took a year-long sequence in statistical methods. Popular choices of the course text book in that period prior to the availability of high speed computing and graphics capability were those authored by Snedecor and Cochran, and Steel and Torrie. By 1980, the topical coverage in these classics failed to include a great many new and important elementary techniques in the data analyst's toolkit. In order to teach the statistical methods sequence with adequate coverage of topics, it became necessary to draw material from each of four or five text sources. Obviously, such a situation makes life difficult for both students and instructors. In addition, statistics students need to become proficient with at least one high-quality statistical software package. This book can serve as a standalone text for a contemporary year-long course in statistical methods at a level appropriate for statistics majors at the master's level or other quantitatively oriented disciplines at the doctoral level. The topics include both concepts and techniques developed many years ago and a variety of newer tools not commonly found in textbooks.
Handbook Of Statistical Analysis And Data Mining Applications
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Author : Ken Yale
language : en
Publisher: Elsevier
Release Date : 2017-11-09
Handbook Of Statistical Analysis And Data Mining Applications written by Ken Yale and has been published by Elsevier this book supported file pdf, txt, epub, kindle and other format this book has been release on 2017-11-09 with Mathematics categories.
Handbook of Statistical Analysis and Data Mining Applications, Second Edition, is a comprehensive professional reference book that guides business analysts, scientists, engineers and researchers, both academic and industrial, through all stages of data analysis, model building and implementation. The handbook helps users discern technical and business problems, understand the strengths and weaknesses of modern data mining algorithms and employ the right statistical methods for practical application. This book is an ideal reference for users who want to address massive and complex datasets with novel statistical approaches and be able to objectively evaluate analyses and solutions. It has clear, intuitive explanations of the principles and tools for solving problems using modern analytic techniques and discusses their application to real problems in ways accessible and beneficial to practitioners across several areas—from science and engineering, to medicine, academia and commerce. - Includes input by practitioners for practitioners - Includes tutorials in numerous fields of study that provide step-by-step instruction on how to use supplied tools to build models - Contains practical advice from successful real-world implementations - Brings together, in a single resource, all the information a beginner needs to understand the tools and issues in data mining to build successful data mining solutions - Features clear, intuitive explanations of novel analytical tools and techniques, and their practical applications
Computational And Statistical Methods For Analysing Big Data With Applications
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Author : Shen Liu
language : en
Publisher: Academic Press
Release Date : 2015-11-20
Computational And Statistical Methods For Analysing Big Data With Applications written by Shen Liu and has been published by Academic Press this book supported file pdf, txt, epub, kindle and other format this book has been release on 2015-11-20 with Mathematics categories.
Due to the scale and complexity of data sets currently being collected in areas such as health, transportation, environmental science, engineering, information technology, business and finance, modern quantitative analysts are seeking improved and appropriate computational and statistical methods to explore, model and draw inferences from big data. This book aims to introduce suitable approaches for such endeavours, providing applications and case studies for the purpose of demonstration. Computational and Statistical Methods for Analysing Big Data with Applications starts with an overview of the era of big data. It then goes onto explain the computational and statistical methods which have been commonly applied in the big data revolution. For each of these methods, an example is provided as a guide to its application. Five case studies are presented next, focusing on computer vision with massive training data, spatial data analysis, advanced experimental design methods for big data, big data in clinical medicine, and analysing data collected from mobile devices, respectively. The book concludes with some final thoughts and suggested areas for future research in big data. - Advanced computational and statistical methodologies for analysing big data are developed - Experimental design methodologies are described and implemented to make the analysis of big data more computationally tractable - Case studies are discussed to demonstrate the implementation of the developed methods - Five high-impact areas of application are studied: computer vision, geosciences, commerce, healthcare and transportation - Computing code/programs are provided where appropriate