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Applied Statistical Modeling and Data Analytics

Applied Statistical Modeling and Data Analytics
  • Author : Srikanta Mishra,Akhil Datta-Gupta
  • Publisher : Elsevier
  • Release : 27 October 2017
GET THIS BOOKApplied Statistical Modeling and Data Analytics

Applied Statistical Modeling and Data Analytics: A Practical Guide for the Petroleum Geosciences provides a practical guide to many of the classical and modern statistical techniques that have become established for oil and gas professionals in recent years. It serves as a "how to" reference volume for the practicing petroleum engineer or geoscientist interested in applying statistical methods in formation evaluation, reservoir characterization, reservoir modeling and management, and uncertainty quantification. Beginning with a foundational discussion of exploratory data analysis, probability

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Applied Modeling Techniques and Data Analysis 2

Applied Modeling Techniques and Data Analysis 2
  • Author : Yannis Dimotikalis,Alex Karagrigoriou,Christina Parpoula,Christos H. Skiadas
  • Publisher : John Wiley & Sons
  • Release : 11 May 2021
GET THIS BOOKApplied Modeling Techniques and Data Analysis 2

BIG DATA, ARTIFICIAL INTELLIGENCE AND DATA ANALYSIS SET Coordinated by Jacques Janssen Data analysis is a scientific field that continues to grow enormously, most notably over the last few decades, following rapid growth within the tech industry, as well as the wide applicability of computational techniques alongside new advances in analytic tools. Modeling enables data analysts to identify relationships, make predictions, and to understand, interpret and visualize the extracted information more strategically. This book includes the most recent advances on

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Applied Data Analysis and Modeling for Energy Engineers and Scientists

Applied Data Analysis and Modeling for Energy Engineers and Scientists
  • Author : T. Agami Reddy
  • Publisher : Springer Science & Business Media
  • Release : 09 August 2011
GET THIS BOOKApplied Data Analysis and Modeling for Energy Engineers and Scientists

Applied Data Analysis and Modeling for Energy Engineers and Scientists fills an identified gap in engineering and science education and practice for both students and practitioners. It demonstrates how to apply concepts and methods learned in disparate courses such as mathematical modeling, probability,statistics, experimental design, regression, model building, optimization, risk analysis and decision-making to actual engineering processes and systems. The text provides a formal structure that offers a basic, broad and unified perspective,while imparting the knowledge, skills and

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Statistical Modeling and Analysis for Complex Data Problems

Statistical Modeling and Analysis for Complex Data Problems
  • Author : Pierre Duchesne,Bruno Rémillard
  • Publisher : Springer Science & Business Media
  • Release : 05 December 2005
GET THIS BOOKStatistical Modeling and Analysis for Complex Data Problems

This book reviews some of today’s more complex problems, and reflects some of the important research directions in the field. Twenty-nine authors – largely from Montreal’s GERAD Multi-University Research Center and who work in areas of theoretical statistics, applied statistics, probability theory, and stochastic processes – present survey chapters on various theoretical and applied problems of importance and interest to researchers and students across a number of academic domains.

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Statistical Modelling and Sports Business Analytics

Statistical Modelling and Sports Business Analytics
  • Author : Vanessa Ratten,Ted Hayduk
  • Publisher : Routledge
  • Release : 11 May 2020
GET THIS BOOKStatistical Modelling and Sports Business Analytics

This book introduces predictive analytics in sports and discusses the relationship between analytics and algorithms and statistics. It defines sports data to be used and explains why the unique nature of sports would make analytics useful. The book also explains why the proper use of predictive analytics includes knowing what they are incapable of doing as well as the role of predictive analytics in the bigger picture of sports entrepreneurship, innovation, and technology. The book looks at the mathematical foundations

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Mathematical Modelling and Optimization of Engineering Problems

Mathematical Modelling and Optimization of Engineering Problems
  • Author : J. A. Tenreiro Machado,Necati Özdemir,Dumitru Baleanu
  • Publisher : Springer Nature
  • Release : 12 February 2020
GET THIS BOOKMathematical Modelling and Optimization of Engineering Problems

This book presents recent developments in modelling and optimization of engineering systems and the use of advanced mathematical methods for solving complex real-world problems. It provides recent theoretical developments and new techniques based on control, optimization theory, mathematical modeling and fractional calculus that can be used to model and understand complex behavior in natural phenomena including latest technologies such as additive manufacturing. Specific topics covered in detail include combinatorial optimization, flow and heat transfer, mathematical modelling, energy storage and management

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Applied Predictive Modeling

Applied Predictive Modeling
  • Author : Max Kuhn,Kjell Johnson
  • Publisher : Springer Science & Business Media
  • Release : 17 May 2013
GET THIS BOOKApplied Predictive Modeling

Applied Predictive Modeling covers the overall predictive modeling process, beginning with the crucial steps of data preprocessing, data splitting and foundations of model tuning. The text then provides intuitive explanations of numerous common and modern regression and classification techniques, always with an emphasis on illustrating and solving real data problems. The text illustrates all parts of the modeling process through many hands-on, real-life examples, and every chapter contains extensive R code for each step of the process. This multi-purpose text

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Data Analysis Using Regression and Multilevel/Hierarchical Models

Data Analysis Using Regression and Multilevel/Hierarchical Models
  • Author : Andrew Gelman,Professor in the Department of Statistics Andrew Gelman,Jennifer Hill
  • Publisher : Cambridge University Press
  • Release : 29 November 2021
GET THIS BOOKData Analysis Using Regression and Multilevel/Hierarchical Models

This book, first published in 2007, is for the applied researcher performing data analysis using linear and nonlinear regression and multilevel models.

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Statistical Learning and Modeling in Data Analysis

Statistical Learning and Modeling in Data Analysis
  • Author : Simona Balzano,Giovanni C. Porzio,Renato Salvatore,Domenico Vistocco,Maurizio Vichi
  • Publisher : Springer
  • Release : 14 July 2021
GET THIS BOOKStatistical Learning and Modeling in Data Analysis

The contributions gathered in this book focus on modern methods for statistical learning and modeling in data analysis and present a series of engaging real-world applications. The book covers numerous research topics, ranging from statistical inference and modeling to clustering and factorial methods, from directional data analysis to time series analysis and small area estimation. The applications reflect new analyses in a variety of fields, including medicine, finance, engineering, marketing and cyber risk. The book gathers selected and peer-reviewed contributions

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Advances in Theoretical and Applied Statistics

Advances in Theoretical and Applied Statistics
  • Author : Nicola Torelli,Fortunato Pesarin,Avner Bar-Hen
  • Publisher : Springer Science & Business Media
  • Release : 26 June 2013
GET THIS BOOKAdvances in Theoretical and Applied Statistics

This volume includes contributions selected after a double blind review process and presented as a preliminary version at the 45th Meeting of the Italian Statistical Society. The papers provide significant and innovative original contributions and cover a broad range of topics including: statistical theory; methods for time series and spatial data; statistical modeling and data analysis; survey methodology and official statistics; analysis of social, demographic and health data; and economic statistics and econometrics.

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Statistical Modeling and Analysis for Complex Data Problems

Statistical Modeling and Analysis for Complex Data Problems
  • Author : Pierre Duchesne,Bruno Rémillard
  • Publisher : Springer Science & Business Media
  • Release : 12 April 2005
GET THIS BOOKStatistical Modeling and Analysis for Complex Data Problems

STATISTICAL MODELING AND ANALYSIS FOR COMPLEX DATA PROBLEMS treats some of today’s more complex problems and it reflects some of the important research directions in the field. Twenty-nine authors—largely from Montreal’s GERAD Multi-University Research Center and who work in areas of theoretical statistics, applied statistics, probability theory, and stochastic processes—present survey chapters on various theoretical and applied problems of importance and interest to researchers and students across a number of academic domains. Some of the areas

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Empirical Modeling and Data Analysis for Engineers and Applied Scientists

Empirical Modeling and Data Analysis for Engineers and Applied Scientists
  • Author : Scott A. Pardo
  • Publisher : Springer
  • Release : 19 July 2016
GET THIS BOOKEmpirical Modeling and Data Analysis for Engineers and Applied Scientists

This textbook teaches advanced undergraduate and first-year graduate students in Engineering and Applied Sciences to gather and analyze empirical observations (data) in order to aid in making design decisions. While science is about discovery, the primary paradigm of engineering and "applied science" is design. Scientists are in the discovery business and want, in general, to understand the natural world rather than to alter it. In contrast, engineers and applied scientists design products, processes, and solutions to problems. That said, statistics,

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Managerial Perspectives on Intelligent Big Data Analytics

Managerial Perspectives on Intelligent Big Data Analytics
  • Author : Sun, Zhaohao
  • Publisher : IGI Global
  • Release : 22 February 2019
GET THIS BOOKManagerial Perspectives on Intelligent Big Data Analytics

Big data, analytics, and artificial intelligence are revolutionizing work, management, and lifestyles and are becoming disruptive technologies for healthcare, e-commerce, and web services. However, many fundamental, technological, and managerial issues for developing and applying intelligent big data analytics in these fields have yet to be addressed. Managerial Perspectives on Intelligent Big Data Analytics is a collection of innovative research that discusses the integration and application of artificial intelligence, business intelligence, digital transformation, and intelligent big data analytics from a perspective

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Statistical Methods for the Analysis of Biomedical Data

Statistical Methods for the Analysis of Biomedical Data
  • Author : Robert F. Woolson,William R. Clarke
  • Publisher : John Wiley & Sons
  • Release : 25 January 2011
GET THIS BOOKStatistical Methods for the Analysis of Biomedical Data

The new edition adds a chapter on multiple linear regression inbiomedical research, with sections including the multiple linearregressions model and least squares; the ANOVA table, parameterestimates, and confidence intervals; partial f-tests; polynomialregression; and analysis of covariance. * Organized by problem rather than method, so it guides readers tothe correct technique for solving the problem at hand.

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Modelling and Implementation of Complex Systems

Modelling and Implementation of Complex Systems
  • Author : Salim Chikhi,Abdelmalek Amine,Allaoua Chaoui,Djamel Eddine Saidouni,Mohamed Khireddine Kholladi
  • Publisher : Springer Nature
  • Release : 05 September 2020
GET THIS BOOKModelling and Implementation of Complex Systems

This proceedings book gives a new vision and real progress towards more difficult problems resolution. In trying to solve the problems we face every day in the complex world we are living, we are constantly developing artificial systems and increasingly complex middleware. Indeed, the research works contained in this book address a large spread of nowadays topics like IoT architectures, communication and routing protocols, smart systems, software defined networks (SDNs), natural language processing (NLP), social media, health systems, machine intelligence

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