Applied Statistical Modeling and Data Analytics

Applied Statistical Modeling and Data Analytics
Author :
Publisher : Elsevier
Total Pages : 252
Release :
ISBN-10 : 9780128032800
ISBN-13 : 0128032804
Rating : 4/5 (804 Downloads)

Book Synopsis Applied Statistical Modeling and Data Analytics by : Srikanta Mishra

Download or read book Applied Statistical Modeling and Data Analytics written by Srikanta Mishra and published by Elsevier. This book was released on 2017-10-27 with total page 252 pages. Available in PDF, EPUB and Kindle. Book excerpt: 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


Applied Statistical Modeling and Data Analytics Related Books

Applied Statistical Modeling and Data Analytics
Language: en
Pages: 252
Authors: Srikanta Mishra
Categories: Science
Type: BOOK - Published: 2017-10-27 - Publisher: Elsevier

DOWNLOAD EBOOK

Applied Statistical Modeling and Data Analytics: A Practical Guide for the Petroleum Geosciences provides a practical guide to many of the classical and modern
Applied Predictive Modeling
Language: en
Pages: 595
Authors: Max Kuhn
Categories: Medical
Type: BOOK - Published: 2013-05-17 - Publisher: Springer Science & Business Media

DOWNLOAD EBOOK

Applied Predictive Modeling covers the overall predictive modeling process, beginning with the crucial steps of data preprocessing, data splitting and foundatio
Empirical Modeling and Data Analysis for Engineers and Applied Scientists
Language: en
Pages: 255
Authors: Scott A. Pardo
Categories: Mathematics
Type: BOOK - Published: 2016-07-19 - Publisher: Springer

DOWNLOAD EBOOK

This textbook teaches advanced undergraduate and first-year graduate students in Engineering and Applied Sciences to gather and analyze empirical observations (
Applied Linear Statistical Models
Language: en
Pages: 1396
Authors: Michael H. Kutner
Categories: Mathematics
Type: BOOK - Published: 2005 - Publisher: McGraw-Hill/Irwin

DOWNLOAD EBOOK

Linear regression with one predictor variable; Inferences in regression and correlation analysis; Diagnosticis and remedial measures; Simultaneous inferences an
Applied Data Analysis and Modeling for Energy Engineers and Scientists
Language: en
Pages: 446
Authors: T. Agami Reddy
Categories: Technology & Engineering
Type: BOOK - Published: 2011-08-09 - Publisher: Springer Science & Business Media

DOWNLOAD EBOOK

Applied Data Analysis and Modeling for Energy Engineers and Scientists fills an identified gap in engineering and science education and practice for both studen