Exploring Binary Outcome Data By Logistic Regression Model And Generalized Additive Logistic Model
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Exploring Binary Outcome Data By Logistic Regression Model And Generalized Additive Logistic Model
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Author : Hiba Abdalla Ibrahim
language : en
Publisher:
Release Date : 2005
Exploring Binary Outcome Data By Logistic Regression Model And Generalized Additive Logistic Model written by Hiba Abdalla Ibrahim and has been published by this book supported file pdf, txt, epub, kindle and other format this book has been release on 2005 with Linear models (Statistics) categories.
Generalized Additive Models
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Author : Simon N. Wood
language : en
Publisher: CRC Press
Release Date : 2006-02-27
Generalized Additive Models written by Simon N. Wood and has been published by CRC Press this book supported file pdf, txt, epub, kindle and other format this book has been release on 2006-02-27 with Mathematics categories.
Now in widespread use, generalized additive models (GAMs) have evolved into a standard statistical methodology of considerable flexibility. While Hastie and Tibshirani's outstanding 1990 research monograph on GAMs is largely responsible for this, there has been a long-standing need for an accessible introductory treatment of the subject that also e
Telling Stories With Data
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Author : Rohan Alexander
language : en
Publisher: CRC Press
Release Date : 2023-07-27
Telling Stories With Data written by Rohan Alexander and has been published by CRC Press this book supported file pdf, txt, epub, kindle and other format this book has been release on 2023-07-27 with Business & Economics categories.
The book equips students with the end-to-end skills needed to do data science. That means gathering, cleaning, preparing, and sharing data, then using statistical models to analyse data, writing about the results of those models, drawing conclusions from them, and finally, using the cloud to put a model into production, all done in a reproducible way. At the moment, there are a lot of books that teach data science, but most of them assume that you already have the data. This book fills that gap by detailing how to go about gathering datasets, cleaning and preparing them, before analysing them. There are also a lot of books that teach statistical modelling, but few of them teach how to communicate the results of the models and how they help us learn about the world. Very few data science textbooks cover ethics, and most of those that do, have a token ethics chapter. Finally, reproducibility is not often emphasised in data science books. This book is based around a straight-forward workflow conducted in an ethical and reproducible way: gather data, prepare data, analyse data, and communicate those findings. This book will achieve the goals by working through extensive case studies in terms of gathering and preparing data, and integrating ethics throughout. It is specifically designed around teaching how to write about the data and models, so aspects such as writing are explicitly covered. And finally, the use of GitHub and the open-source statistical language R are built in throughout the book. Key Features: Extensive code examples. Ethics integrated throughout. Reproducibility integrated throughout. Focus on data gathering, messy data, and cleaning data. Extensive formative assessment throughout.
Key Topics In Surgical Research And Methodology
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Author : Thanos Athanasiou
language : en
Publisher: Springer Science & Business Media
Release Date : 2010-02-28
Key Topics In Surgical Research And Methodology written by Thanos Athanasiou and has been published by Springer Science & Business Media this book supported file pdf, txt, epub, kindle and other format this book has been release on 2010-02-28 with Medical categories.
Key Topics in Surgical Research and Methodology represents a comprehensive reference text accessible to the surgeon embarking on an academic career. Key themes emphasize and summarize the text. Four key elements are covered, i.e. Surgical Research, Research Methodology, Practical Problems and Solutions on Research as well as Recent Developments and Future Prospects in Surgical Research and Practice.
Enhance Oil And Gas Exploration With Data Driven Geophysical And Petrophysical Models
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Author : Keith R. Holdaway
language : en
Publisher: John Wiley & Sons
Release Date : 2017-10-04
Enhance Oil And Gas Exploration With Data Driven Geophysical And Petrophysical Models written by Keith R. Holdaway and has been published by John Wiley & Sons this book supported file pdf, txt, epub, kindle and other format this book has been release on 2017-10-04 with Business & Economics categories.
Leverage Big Data analytics methodologies to add value to geophysical and petrophysical exploration data Enhance Oil & Gas Exploration with Data-Driven Geophysical and Petrophysical Models demonstrates a new approach to geophysics and petrophysics data analysis using the latest methods drawn from Big Data. Written by two geophysicists with a combined 30 years in the industry, this book shows you how to leverage continually maturing computational intelligence to gain deeper insight from specific exploration data. Case studies illustrate the value propositions of this alternative analytical workflow, and in-depth discussion addresses the many Big Data issues in geophysics and petrophysics. From data collection and context through real-world everyday applications, this book provides an essential resource for anyone involved in oil and gas exploration. Recent and continual advances in machine learning are driving a rapid increase in empirical modeling capabilities. This book shows you how these new tools and methodologies can enhance geophysical and petrophysical data analysis, increasing the value of your exploration data. Apply data-driven modeling concepts in a geophysical and petrophysical context Learn how to get more information out of models and simulations Add value to everyday tasks with the appropriate Big Data application Adjust methodology to suit diverse geophysical and petrophysical contexts Data-driven modeling focuses on analyzing the total data within a system, with the goal of uncovering connections between input and output without definitive knowledge of the system's physical behavior. This multi-faceted approach pushes the boundaries of conventional modeling, and brings diverse fields of study together to apply new information and technology in new and more valuable ways. Enhance Oil & Gas Exploration with Data-Driven Geophysical and Petrophysical Models takes you beyond traditional deterministic interpretation to the future of exploration data analysis.
Case Studies In Bayesian Statistics
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Author : Constantine Gatsonis
language : en
Publisher: Springer
Release Date : 2018-08-17
Case Studies In Bayesian Statistics written by Constantine Gatsonis and has been published by Springer this book supported file pdf, txt, epub, kindle and other format this book has been release on 2018-08-17 with Mathematics categories.
The 6th Workshop on Case Studies in Bayesian Statistics was held at the Carnegie Mellon University in October, 2001. This volume contains the invited case studies with the accompanying discussion as well as contributed papers selected by a refereeing process.
Big Data Analytics Methods
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Author : Peter Ghavami
language : en
Publisher: Walter de Gruyter GmbH & Co KG
Release Date : 2019-12-16
Big Data Analytics Methods written by Peter Ghavami and has been published by Walter de Gruyter GmbH & Co KG this book supported file pdf, txt, epub, kindle and other format this book has been release on 2019-12-16 with Business & Economics categories.
Big Data Analytics Methods unveils secrets to advanced analytics techniques ranging from machine learning, random forest classifiers, predictive modeling, cluster analysis, natural language processing (NLP), Kalman filtering and ensembles of models for optimal accuracy of analysis and prediction. More than 100 analytics techniques and methods provide big data professionals, business intelligence professionals and citizen data scientists insight on how to overcome challenges and avoid common pitfalls and traps in data analytics. The book offers solutions and tips on handling missing data, noisy and dirty data, error reduction and boosting signal to reduce noise. It discusses data visualization, prediction, optimization, artificial intelligence, regression analysis, the Cox hazard model and many analytics using case examples with applications in the healthcare, transportation, retail, telecommunication, consulting, manufacturing, energy and financial services industries. This book's state of the art treatment of advanced data analytics methods and important best practices will help readers succeed in data analytics.
Geostatistics Wollongong 96
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Author : Ernest Y. Baafi
language : en
Publisher: Springer Science & Business Media
Release Date : 1997
Geostatistics Wollongong 96 written by Ernest Y. Baafi and has been published by Springer Science & Business Media this book supported file pdf, txt, epub, kindle and other format this book has been release on 1997 with Science categories.
The papers in this volume provide a comprehensive account of the current methods and work in geostatistics, including recent theoretical developments and applications. Topics featured include: stochastic simulations, space-time modelling, and Bayesian framework.
Data Science And Big Data Analytics
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Author : EMC Education Services
language : en
Publisher: John Wiley & Sons
Release Date : 2015-01-05
Data Science And Big Data Analytics written by EMC Education Services and has been published by John Wiley & Sons this book supported file pdf, txt, epub, kindle and other format this book has been release on 2015-01-05 with Computers categories.
Data Science and Big Data Analytics is about harnessing the power of data for new insights. The book covers the breadth of activities and methods and tools that Data Scientists use. The content focuses on concepts, principles and practical applications that are applicable to any industry and technology environment, and the learning is supported and explained with examples that you can replicate using open-source software. This book will help you: Become a contributor on a data science team Deploy a structured lifecycle approach to data analytics problems Apply appropriate analytic techniques and tools to analyzing big data Learn how to tell a compelling story with data to drive business action Prepare for EMC Proven Professional Data Science Certification Get started discovering, analyzing, visualizing, and presenting data in a meaningful way today!
Statistical Methods For Mediation Confounding And Moderation Analysis Using R And Sas
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Author : Qingzhao Yu
language : en
Publisher: CRC Press
Release Date : 2022-03-14
Statistical Methods For Mediation Confounding And Moderation Analysis Using R And Sas written by Qingzhao Yu and has been published by CRC Press this book supported file pdf, txt, epub, kindle and other format this book has been release on 2022-03-14 with Mathematics categories.
Third-variable effect refers to the effect transmitted by third-variables that intervene in the relationship between an exposure and a response variable. Differentiating between the indirect effect of individual factors from multiple third-variables is a constant problem for modern researchers. Statistical Methods for Mediation, Confounding and Moderation Analysis Using R and SAS introduces general definitions of third-variable effects that are adaptable to all different types of response (categorical or continuous), exposure, or third-variables. Using this method, multiple third- variables of different types can be considered simultaneously, and the indirect effect carried by individual third-variables can be separated from the total effect. Readers of all disciplines familiar with introductory statistics will find this a valuable resource for analysis. Key Features: Parametric and nonparametric method in third variable analysis Multivariate and Multiple third-variable effect analysis Multilevel mediation/confounding analysis Third-variable effect analysis with high-dimensional data Moderation/Interaction effect analysis within the third-variable analysis R packages and SAS macros to implement methods proposed in the book