Applied 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 distributions and linear regression modeling, the book focuses on fundamentals and practical examples of such key topics as multivariate analysis, uncertainty quantification, data-driven modeling, and experimental design and response surface analysis. Data sets from the petroleum geosciences are extensively used to demonstrate the applicability of these techniques. The book will also be useful for professionals dealing with subsurface flow problems in hydrogeology, geologic carbon sequestration, and nuclear waste disposal. Authored by internationally renowned experts in developing and applying statistical methods for oil & gas and other subsurface problem domains Written by practitioners for practitioners Presents an easy to follow narrative which progresses from simple concepts to more challenging ones Includes online resources with software applications and practical examples for the most relevant and popular statistical methods, using data sets from the petroleum geosciences Addresses the theory and practice of statistical modeling and data analytics from the perspective of petroleum geoscience applications

Produk Detail:

  • Author : Srikanta Mishra
  • Publisher : Elsevier
  • Pages : 250 pages
  • ISBN : 0128032804
  • Rating : 4/5 from 21 reviews
CLICK HERE TO GET THIS BOOKApplied Statistical Modeling and Data Analytics

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

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

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

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

Applied Predictive Analytics

Applied Predictive Analytics
  • Author : Dean Abbott
  • Publisher : John Wiley & Sons
  • Release : 31 March 2014
GET THIS BOOKApplied Predictive Analytics

Learn the art and science of predictive analytics — techniques that get results Predictive analytics is what translates big data into meaningful, usable business information. Written by a leading expert in the field, this guide examines the science of the underlying algorithms as well as the principles and best practices that govern the art of predictive analytics. It clearly explains the theory behind predictive analytics, teaches the methods, principles, and techniques for conducting predictive analytics projects, and offers tips and tricks

Applied Analytics through Case Studies Using SAS and R

Applied Analytics through Case Studies Using SAS and R
  • Author : Deepti Gupta
  • Publisher : Apress
  • Release : 03 August 2018
GET THIS BOOKApplied Analytics through Case Studies Using SAS and R

Examine business problems and use a practical analytical approach to solve them by implementing predictive models and machine learning techniques using SAS and the R analytical language. This book is ideal for those who are well-versed in writing code and have a basic understanding of statistics, but have limited experience in implementing predictive models and machine learning techniques for analyzing real world data. The most challenging part of solving industrial business problems is the practical and hands-on knowledge of building

Applied Data Mining

Applied Data Mining
  • Author : Paolo Giudici
  • Publisher : John Wiley & Sons
  • Release : 27 September 2005
GET THIS BOOKApplied Data Mining

Data mining can be defined as the process of selection, exploration and modelling of large databases, in order to discover models and patterns. The increasing availability of data in the current information 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 such knowledge from data. Applications occur in many different fields, including statistics, computer science, machine learning, economics, marketing and finance. This book

Applied Data Analytics - Principles and Applications

Applied Data Analytics - Principles and Applications
  • Author : Johnson I. Agbinya
  • Publisher : River Publishers Signal, Image
  • Release : 30 July 2019
GET THIS BOOKApplied Data Analytics - Principles and Applications

The emergence of huge amounts of data which require analysis and in some cases real-time processing has forced exploration into fast algorithms for handling very large data sizes. Analysis of x-ray images in medical applications, cyber security data, crime data, telecommunications and stock market data, health records and business analytics data are but a few areas of interest. Applications and platforms including R, RapidMiner and Weka provide the basis for analysis, often used by practitioners who pay little to no

Harness Oil and Gas Big Data with Analytics

Harness Oil and Gas Big Data with Analytics
  • Author : Keith R. Holdaway
  • Publisher : John Wiley & Sons
  • Release : 05 May 2014
GET THIS BOOKHarness Oil and Gas Big Data with Analytics

Use big data analytics to efficiently drive oil and gas exploration and production Harness Oil and Gas Big Data with Analytics provides a complete view of big data and analytics techniques as they are applied to the oil and gas industry. Including a compendium of specific case studies, the book underscores the acute need for optimization in the oil and gas exploration and production stages and shows how data analytics can provide such optimization. This spans exploration, development, production and

Handbook of Statistical Analysis and Data Mining Applications

Handbook of Statistical Analysis and Data Mining Applications
  • Author : Robert Nisbet,Gary Miner,Ken Yale
  • Publisher : Elsevier
  • Release : 09 November 2017
GET THIS BOOKHandbook of Statistical Analysis and Data Mining Applications

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

Statistical Models for Data Analysis

Statistical Models for Data Analysis
  • Author : Paolo Giudici,Salvatore Ingrassia,Maurizio Vichi
  • Publisher : Springer Science & Business Media
  • Release : 01 July 2013
GET THIS BOOKStatistical Models for Data Analysis

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. ​

Advances in Statistical Models for Data Analysis

Advances in Statistical Models for Data Analysis
  • Author : Isabella Morlini,Tommaso Minerva,Maurizio Vichi
  • Publisher : Springer
  • Release : 04 September 2015
GET THIS BOOKAdvances in Statistical Models for Data Analysis

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

Statistical Data Analysis Using SAS

Statistical Data Analysis Using SAS
  • Author : Mervyn G. Marasinghe,Kenneth J. Koehler
  • Publisher : Springer
  • Release : 12 April 2018
GET THIS BOOKStatistical Data Analysis Using SAS

The aim of this textbook (previously titled SAS for Data Analytics) is to teach the use of SAS for statistical analysis of data for advanced undergraduate and graduate students in statistics, data science, and disciplines involving analyzing data. The book begins with an introduction beyond the basics of SAS, illustrated with non-trivial, real-world, worked examples. It proceeds to SAS programming and applications, SAS graphics, statistical analysis of regression models, analysis of variance models, analysis of variance with random and mixed

Mobility Patterns, Big Data and Transport Analytics

Mobility Patterns, Big Data and Transport Analytics
  • Author : Constantinos Antoniou,Loukas Dimitriou,Francisco Pereira
  • Publisher : Elsevier
  • Release : 27 November 2018
GET THIS BOOKMobility Patterns, Big Data and Transport Analytics

Mobility Patterns, Big Data and Transport Analytics provides a guide to the new analytical framework and its relation to big data, focusing on capturing, predicting, visualizing and controlling mobility patterns - a key aspect of transportation modeling. The book features prominent international experts who provide overviews on new analytical frameworks, applications and concepts in mobility analysis and transportation systems. Users will find a detailed, mobility ‘structural’ analysis and a look at the extensive behavioral characteristics of transport, observability requirements and

Spatial Regression Models

Spatial Regression Models
  • Author : Michael D. Ward,Kristian Skrede Gleditsch
  • Publisher : SAGE Publications
  • Release : 10 April 2018
GET THIS BOOKSpatial Regression Models

Spatial Regression Models illustrates the use of spatial analysis in the social sciences within a regression framework and is accessible to readers with no prior background in spatial analysis. The text covers different modeling-related topics for continuous dependent variables, including mapping data on spatial units, creating data from maps, analyzing exploratory spatial data, working with regression models that have spatially dependent regressors, and estimating regression models with spatially correlated error structures. Using social science examples based on real data, the