New Perspectives in Statistical Modeling and Data Analysis PDF Download

Author: Salvatore Ingrassia
Publisher: Springer Science & Business Media
ISBN: 364211363X
Category : Mathematics
Languages : en
Pages : 576

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Book Description
This volume provides recent research results in data analysis, classification and multivariate statistics and highlights perspectives for new scientific developments within these areas. Particular attention is devoted to methodological issues in clustering, statistical modeling and data mining. The volume also contains significant contributions to a wide range of applications such as finance, marketing, and social sciences. The papers in this volume were first presented at the 7th Conference of the Classification and Data Analysis Group (ClaDAG) of the Italian Statistical Society, held at the University of Catania, Italy.

Author: Bruce Ratner
Publisher: CRC Press
ISBN: 0203496906
Category : Business & Economics
Languages : en
Pages : 383

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Book Description
Traditional statistical methods are limited in their ability to meet the modern challenge of mining large amounts of data. Data miners, analysts, and statisticians are searching for innovative new data mining techniques with greater predictive power, an attribute critical for reliable models and analyses. Statistical Modeling and Analysis fo

Author: Cathy O'Neil
Publisher: "O'Reilly Media, Inc."
ISBN: 144936389X
Category : Computers
Languages : en
Pages : 320

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Book Description
Now that people are aware that data can make the difference in an election or a business model, data science as an occupation is gaining ground. But how can you get started working in a wide-ranging, interdisciplinary field that’s so clouded in hype? This insightful book, based on Columbia University’s Introduction to Data Science class, tells you what you need to know. In many of these chapter-long lectures, data scientists from companies such as Google, Microsoft, and eBay share new algorithms, methods, and models by presenting case studies and the code they use. If you’re familiar with linear algebra, probability, and statistics, and have programming experience, this book is an ideal introduction to data science. Topics include: Statistical inference, exploratory data analysis, and the data science process Algorithms Spam filters, Naive Bayes, and data wrangling Logistic regression Financial modeling Recommendation engines and causality Data visualization Social networks and data journalism Data engineering, MapReduce, Pregel, and Hadoop Doing Data Science is collaboration between course instructor Rachel Schutt, Senior VP of Data Science at News Corp, and data science consultant Cathy O’Neil, a senior data scientist at Johnson Research Labs, who attended and blogged about the course.

Author: Paolo Giudici
Publisher: Springer Science & Business Media
ISBN: 3319000322
Category : Mathematics
Languages : en
Pages : 413

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Book Description
The papers in this book cover issues related to the development of novel statistical models for the analysis of data. They offer solutions for relevant problems in statistical data analysis and contain the explicit derivation of the proposed models as well as their implementation. The book assembles the selected and refereed proceedings of the biannual conference of the Italian Classification and Data Analysis Group (CLADAG), a section of the Italian Statistical Society. ​

Author: Isabella Morlini
Publisher: Springer
ISBN: 3319173774
Category : Mathematics
Languages : en
Pages : 264

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Book Description
This edited volume focuses on recent research results in classification, multivariate statistics and machine learning and highlights advances in statistical models for data analysis. The volume provides both methodological developments and contributions to a wide range of application areas such as economics, marketing, education, social sciences and environment. The papers in this volume were first presented at the 9th biannual meeting of the Classification and Data Analysis Group (CLADAG) of the Italian Statistical Society, held in September 2013 at the University of Modena and Reggio Emilia, Italy.

Author: Deborah G. Mayo
Publisher: Cambridge University Press
ISBN: 1108563309
Category : Mathematics
Languages : en
Pages : 503

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Book Description
Mounting failures of replication in social and biological sciences give a new urgency to critically appraising proposed reforms. This book pulls back the cover on disagreements between experts charged with restoring integrity to science. It denies two pervasive views of the role of probability in inference: to assign degrees of belief, and to control error rates in a long run. If statistical consumers are unaware of assumptions behind rival evidence reforms, they can't scrutinize the consequences that affect them (in personalized medicine, psychology, etc.). The book sets sail with a simple tool: if little has been done to rule out flaws in inferring a claim, then it has not passed a severe test. Many methods advocated by data experts do not stand up to severe scrutiny and are in tension with successful strategies for blocking or accounting for cherry picking and selective reporting. Through a series of excursions and exhibits, the philosophy and history of inductive inference come alive. Philosophical tools are put to work to solve problems about science and pseudoscience, induction and falsification.

Author: Khosrow-Pour, Mehdi
Publisher: IGI Global
ISBN: 1466660996
Category : Computers
Languages : en
Pages : 379

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Book Description
In the digital age, technological solutions are being developed and integrated into every aspect of our everyday lives. The ever-changing scope of research in systems and software advancements allows for further improvements and applications. Systems and Software Development, Modeling, and Analysis: New Perspectives and Methodologies presents diverse, interdisciplinary research on topics pertaining to the management, integration, evaluation, and architecture of modern computational systems and software. Presenting the most up-to-date research in this rapidly evolving field, this title is ideally designed for use by computer engineers, academicians, graduate and post-graduate students, and computer science researchers.

Author: Álvaro Rocha
Publisher: Springer Nature
ISBN: 3031602277
Category :
Languages : en
Pages : 326

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Book Description

Author: Daniel Navarro
Publisher: Lulu.com
ISBN: 1326189727
Category : Computers
Languages : en
Pages : 617

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Book Description
"Learning Statistics with R" covers the contents of an introductory statistics class, as typically taught to undergraduate psychology students, focusing on the use of the R statistical software and adopting a light, conversational style throughout. The book discusses how to get started in R, and gives an introduction to data manipulation and writing scripts. From a statistical perspective, the book discusses descriptive statistics and graphing first, followed by chapters on probability theory, sampling and estimation, and null hypothesis testing. After introducing the theory, the book covers the analysis of contingency tables, t-tests, ANOVAs and regression. Bayesian statistics are covered at the end of the book. For more information (and the opportunity to check the book out before you buy!) visit http://ua.edu.au/ccs/teaching/lsr or http://learningstatisticswithr.com

Author: Šárka Hošková-Mayerová
Publisher: Springer
ISBN: 3319548190
Category : Technology & Engineering
Languages : en
Pages : 435

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Book Description
This book presents a broad spectrum of problems related to statistics, mathematics, teaching, social science, and economics as well as a range of tools and techniques that can be used to solve these problems. It is the result of a scientific collaboration between experts in the field of economic and social systems from the University of Defence in Brno (Czech Republic), G. d’Annunzio University of Chieti-Pescara (Italy), Pablo de Olavid eUniversity of Sevilla (Spain), and Ovidius University in Constanţa, (Romania). The studies included were selected using a peer-review process and reflect heterogeneity and complexity of economic and social phenomena. They and present interesting empirical research from around the globe and from several research fields, such as statistics, decision making, mathematics, complexity, psychology, sociology and economics. The volume is divided into two parts. The first part, “Recent trends in mathematical and statistical models for economic and social sciences”, collects papers on quantitative matters, which propose mathematical and statistical models for social sciences, economics, finance, and business administration. The second part, “Recent trends in qualitative theories for economic and social sciences”, includes papers on qualitative matters, which discuss social, economic, and teaching issues. It is an ideal reference work for all those researchers interested in recent quantitative and qualitative tools. Covering a wide range of topics, it appeals in equal measure to mathematicians, statisticians, sociologists, philosophers, and specialists in the fields of communication, social and political sciences.