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
Statistical Data Analysis
Language: en
Pages: 218
Authors: Glen Cowan
Categories: Mathematics
Type: BOOK - Published: 1998 - Publisher: Oxford University Press

DOWNLOAD EBOOK

This book is a guide to the practical application of statistics in data analysis as typically encountered in the physical sciences. It is primarily addressed at
Introduction to Statistics and Data Analysis
Language: en
Pages: 584
Authors: Christian Heumann
Categories: Mathematics
Type: BOOK - Published: 2023-01-30 - Publisher: Springer Nature

DOWNLOAD EBOOK

Now in its second edition, this introductory statistics textbook conveys the essential concepts and tools needed to develop and nurture statistical thinking. It
Statistical Data Analysis
Language: en
Pages: 0
Authors: Milan Meloun
Categories: Chemical engineering
Type: BOOK - Published: 2011 - Publisher: Woodhead Publishing Limited

DOWNLOAD EBOOK

Over the past decade, computer supported data analysis by statistical methods has been one of the fastest growth areas in chemometrics, biometrics and other rel
Practical Statistics for Data Scientists
Language: en
Pages: 322
Authors: Peter Bruce
Categories: Computers
Type: BOOK - Published: 2017-05-10 - Publisher: "O'Reilly Media, Inc."

DOWNLOAD EBOOK

Statistical methods are a key part of of data science, yet very few data scientists have any formal statistics training. Courses and books on basic statistics r