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1000 tulosta hakusanalla Daniel R. Faust

Modern Data Science with R

Modern Data Science with R

Benjamin S. Baumer; Daniel T. Kaplan; Nicholas J. Horton

CRC Press
2021
sidottu
From a review of the first edition: "Modern Data Science with R… is rich with examples and is guided by a strong narrative voice. What’s more, it presents an organizing framework that makes a convincing argument that data science is a course distinct from applied statistics" (The American Statistician).Modern Data Science with R is a comprehensive data science textbook for undergraduates that incorporates statistical and computational thinking to solve real-world data problems. Rather than focus exclusively on case studies or programming syntax, this book illustrates how statistical programming in the state-of-the-art R/RStudio computing environment can be leveraged to extract meaningful information from a variety of data in the service of addressing compelling questions.The second edition is updated to reflect the growing influence of the tidyverse set of packages. All code in the book has been revised and styled to be more readable and easier to understand. New functionality from packages like sf, purrr, tidymodels, and tidytext is now integrated into the text. All chapters have been revised, and several have been split, re-organized, or re-imagined to meet the shifting landscape of best practice.
Dose-Response Analysis Using R

Dose-Response Analysis Using R

Christian Ritz; Signe Marie Jensen; Daniel Gerhard; Jens Carl Streibig

Taylor Francis Ltd
2021
nidottu
Nowadays the term dose-response is used in many different contexts and many different scientific disciplines including agriculture, biochemistry, chemistry, environmental sciences, genetics, pharmacology, plant sciences, toxicology, and zoology.In the 1940 and 1950s, dose-response analysis was intimately linked to evaluation of toxicity in terms of binary responses, such as immobility and mortality, with a limited number of doses of a toxic compound being compared to a control group (dose 0). Later, dose-response analysis has been extended to other types of data and to more complex experimental designs. Moreover, estimation of model parameters has undergone a dramatic change, from struggling with cumbersome manual operations and transformations with pen and paper to rapid calculations on any laptop. Advances in statistical software have fueled this development.Key Features: Provides a practical and comprehensive overview of dose-response analysis. Includes numerous real data examples to illustrate the methodology. R code is integrated into the text to give guidance on applying the methods. Written with minimal mathematics to be suitable for practitioners. Includes code and datasets on the book’s GitHub: https://github.com/DoseResponse. This book focuses on estimation and interpretation of entirely parametric nonlinear dose-response models using the powerful statistical environment R. Specifically, this book introduces dose-response analysis of continuous, binomial, count, multinomial, and event-time dose-response data. The statistical models used are partly special cases, partly extensions of nonlinear regression models, generalized linear and nonlinear regression models, and nonlinear mixed-effects models (for hierarchical dose-response data). Both simple and complex dose-response experiments will be analyzed.
Data Science Using Python and R

Data Science Using Python and R

Chantal D. Larose; Daniel T. Larose

Wiley-Blackwell
2019
sidottu
Learn data science by doing data science! Data Science Using Python and R will get you plugged into the world’s two most widespread open-source platforms for data science: Python and R. Data science is hot. Bloomberg called data scientist “the hottest job in America.” Python and R are the top two open-source data science tools in the world. In Data Science Using Python and R, you will learn step-by-step how to produce hands-on solutions to real-world business problems, using state-of-the-art techniques. Data Science Using Python and R is written for the general reader with no previous analytics or programming experience. An entire chapter is dedicated to learning the basics of Python and R. Then, each chapter presents step-by-step instructions and walkthroughs for solving data science problems using Python and R. Those with analytics experience will appreciate having a one-stop shop for learning how to do data science using Python and R. Topics covered include data preparation, exploratory data analysis, preparing to model the data, decision trees, model evaluation, misclassification costs, naïve Bayes classification, neural networks, clustering, regression modeling, dimension reduction, and association rules mining. Further, exciting new topics such as random forests and general linear models are also included. The book emphasizes data-driven error costs to enhance profitability, which avoids the common pitfalls that may cost a company millions of dollars. Data Science Using Python and R provides exercises at the end of every chapter, totaling over 500 exercises in the book. Readers will therefore have plenty of opportunity to test their newfound data science skills and expertise. In the Hands-on Analysis exercises, readers are challenged to solve interesting business problems using real-world data sets.
Dose-Response Analysis Using R

Dose-Response Analysis Using R

Christian Ritz; Signe Marie Jensen; Daniel Gerhard; Jens Carl Streibig

CRC Press
2019
sidottu
Nowadays the term dose-response is used in many different contexts and many different scientific disciplines including agriculture, biochemistry, chemistry, environmental sciences, genetics, pharmacology, plant sciences, toxicology, and zoology.In the 1940 and 1950s, dose-response analysis was intimately linked to evaluation of toxicity in terms of binary responses, such as immobility and mortality, with a limited number of doses of a toxic compound being compared to a control group (dose 0). Later, dose-response analysis has been extended to other types of data and to more complex experimental designs. Moreover, estimation of model parameters has undergone a dramatic change, from struggling with cumbersome manual operations and transformations with pen and paper to rapid calculations on any laptop. Advances in statistical software have fueled this development.Key Features: Provides a practical and comprehensive overview of dose-response analysis. Includes numerous real data examples to illustrate the methodology. R code is integrated into the text to give guidance on applying the methods. Written with minimal mathematics to be suitable for practitioners. Includes code and datasets on the book’s GitHub: https://github.com/DoseResponse. This book focuses on estimation and interpretation of entirely parametric nonlinear dose-response models using the powerful statistical environment R. Specifically, this book introduces dose-response analysis of continuous, binomial, count, multinomial, and event-time dose-response data. The statistical models used are partly special cases, partly extensions of nonlinear regression models, generalized linear and nonlinear regression models, and nonlinear mixed-effects models (for hierarchical dose-response data). Both simple and complex dose-response experiments will be analyzed.
El Caldani Discovers R Words (Berkeley Boys Books - El Caldani Missions)

El Caldani Discovers R Words (Berkeley Boys Books - El Caldani Missions)

Elisha Berkeley; Vaughn Berkeley; Daniel Berkeley

C.M. Berkeley Media Group
2022
pokkari
Welcome back to another wonderful set in the beloved Berkeley Boys Series of books. Now you and your child can see our unique illustrations, funny drawings, and fun activities that make learning to read even more fun Berkeley Boys Books - El Caldani Missions This is an exciting new series where a new character is created. He is detective El Caldani He goes on adventures in search of lots of things. These books are not only great for parents and children to learn to read but will also give them ideas for life as they grow older. Grab a copy of the entire set today. You'll be glad you did ===El Caldani Discovers R Words: In this book, you and your child can read about our detective El Caldani. You'll both enjoy reading together about his discovery of R words. Grab this book today
Introduction to R for Quantitative Finance

Introduction to R for Quantitative Finance

Gergely Daroczi; Michael Puhle; Edina Berlinger; Peter Csoka; Daniel Havran; Marton Michaletzky; Zsolt Tulassay; Kata Varadi; Agnes Vidovics-Dancs

Packt Publishing Limited
2013
nidottu
This book is a tutorial guide for new users that aims to help you understand the basics of and become accomplished with the use of R for quantitative finance. If you are looking to use R to solve problems in quantitative finance, then this book is for you. A basic knowledge of financial theory is assumed, but familiarity with R is not required. With a focus on using R to solve a wide range of issues, this book provides useful content for both the R beginner and more experience users.
Paterson'S Roads; Being An Entirely Original And Accurate Description Of All The Direct And Principal Cross Roads In England And Wales, With Part Of The Roads Of Scotland, To Which Are Added Topographical Sketches Of The Several Cities, Market Towns, And R
This book has been considered by academicians and scholars of great significance and value to literature. This forms a part of the knowledge base for future generations. So that the book is never forgotten we have represented this book in a print format as the same form as it was originally first published. Hence any marks or annotations seen are left intentionally to preserve its true nature.
Multivariate Generalized Linear Mixed Models Using R, Second Edition

Multivariate Generalized Linear Mixed Models Using R, Second Edition

Damon Mark Berridge; Robert Crouchley; Daniel Grose

Productivity Press
2021
sidottu
This book provides a foundation for the application of methods for analyzing multivariate generalized linear mixed models using R. It covers the necessary background in GLMs, mixed models, and multivariate data analysis, and combines them to provide methodology for MGLMs. It has a practical focus, with examples throughout, a supplementary R package for all the models, and detailed case studies. The second edition has been updated with an R package for all models and more detailed case studies.
HBR's 10 Must Reads on Managing People (with featured article "Leadership That Gets Results," by Daniel Goleman)

HBR's 10 Must Reads on Managing People (with featured article "Leadership That Gets Results," by Daniel Goleman)

Harvard Business Review; Daniel Goleman; Jon R. Katzenbach; Renee A. Mauborgne; W. Chan Kim

Harvard Business Review Press
2011
pokkari
Managing people is fraught with challenges--even if you're a seasoned manager. Here's how to handle them. If you read nothing else on managing people, read these 10 articles (featuring "Leadership That Gets Results," by Daniel Goleman). We've combed through hundreds of Harvard Business Review articles and selected the most important ones to help you maximize your employees' performance. HBR's 10 Must Reads on Managing People will inspire you to: * Tailor your management styles to fit your people * Motivate with more responsibility, not more money * Support first-time managers * Build trust by soliciting input * Teach smart people how to learn from failure * Build high-performing teams * Manage your boss This collection of best-selling articles includes: featured article "Leadership That Gets Results" by Daniel Goleman, "One More Time: How Do You Motivate Employees?" "The Set-Up-to-Fail Syndrome," "Saving Your Rookie Managers from Themselves," "What Great Managers Do," "Fair Process: Managing in the Knowledge Economy," "Teaching Smart People How to Learn," "How (Un)ethical Are You?" "The Discipline of Teams," and "Managing Your Boss."
HBR's 10 Must Reads on Managing People (with featured article "Leadership That Gets Results," by Daniel Goleman)

HBR's 10 Must Reads on Managing People (with featured article "Leadership That Gets Results," by Daniel Goleman)

Harvard Business Review; Daniel Goleman; Jon R. Katzenbach; Renee A. Mauborgne; W. Chan Kim

Harvard Business Review Press
2011
sidottu
Managing people is fraught with challenges—even if you're a seasoned manager. Here's how to handle them. If you read nothing else on managing people, read these 10 articles (featuring “Leadership That Gets Results,” by Daniel Goleman). We've combed through hundreds of Harvard Business Review articles and selected the most important ones to help you maximize your employees' performance. HBR's 10 Must Reads on Managing People will inspire you to: Tailor your management styles to fit your peopleMotivate with more responsibility, not more moneySupport first-time managersBuild trust by soliciting inputTeach smart people how to learn from failureBuild high-performing teamsManage your boss This collection of best-selling articles includes: featured article "Leadership That Gets Results" by Daniel Goleman, "One More Time: How Do You Motivate Employees?" "The Set-Up-to-Fail Syndrome," "Saving Your Rookie Managers from Themselves," "What Great Managers Do," "Fair Process: Managing in the Knowledge Economy," "Teaching Smart People How to Learn," "How (Un)ethical Are You?" "The Discipline of Teams," and "Managing Your Boss."
Aufgaben und Loesungen zur Statistik fuer Wirtschafts- und Sozialwissenschaften: incl. Software-Umsetzung in SAS und R
Dieses Buch enth lt zu den typischen Themenbereichen der Statistik eine Reihe von Aufgaben mit Musterl sungen und zus tzlich SAS und R Codes, mittels derer die Aufgaben computergest tzt gel st werden k nnen. Das Buch erg nzt das Textbuch "Understanding Statistics and Probability - An Introduction to Methods, Techniques and Computer Applications" von Daniel R sch und ist an dessen Gliederung und Notation angelehnt. Es wird empfohlen, zun chst das Textbuch durchzuarbeiten, grunds tzlich kann dieses Aufgaben- und L sungsbuch mit entsprechenden Vorkenntnissen aber auch eigenst ndig verwendet werden.
Advanced Spatial Modeling with Stochastic Partial Differential Equations Using R and INLA

Advanced Spatial Modeling with Stochastic Partial Differential Equations Using R and INLA

Elias Krainski; Virgilio Gómez-Rubio; Haakon Bakka; Amanda Lenzi; Daniela Castro-Camilo; Daniel Simpson; Finn Lindgren; Håvard Rue

CRC Press
2020
nidottu
Modeling spatial and spatio-temporal continuous processes is an important and challenging problem in spatial statistics. Advanced Spatial Modeling with Stochastic Partial Differential Equations Using R and INLA describes in detail the stochastic partial differential equations (SPDE) approach for modeling continuous spatial processes with a Matérn covariance, which has been implemented using the integrated nested Laplace approximation (INLA) in the R-INLA package. Key concepts about modeling spatial processes and the SPDE approach are explained with examples using simulated data and real applications.This book has been authored by leading experts in spatial statistics, including the main developers of the INLA and SPDE methodologies and the R-INLA package. It also includes a wide range of applications:* Spatial and spatio-temporal models for continuous outcomes* Analysis of spatial and spatio-temporal point patterns* Coregionalization spatial and spatio-temporal models* Measurement error spatial models* Modeling preferential sampling* Spatial and spatio-temporal models with physical barriers* Survival analysis with spatial effects* Dynamic space-time regression* Spatial and spatio-temporal models for extremes* Hurdle models with spatial effects* Penalized Complexity priors for spatial modelsAll the examples in the book are fully reproducible. Further information about this book, as well as the R code and datasets used, is available from the book website at http://www.r-inla.org/spde-book.The tools described in this book will be useful to researchers in many fields such as biostatistics, spatial statistics, environmental sciences, epidemiology, ecology and others. Graduate and Ph.D. students will also find this book and associated files a valuable resource to learn INLA and the SPDE approach for spatial modeling.
Advanced Spatial Modeling with Stochastic Partial Differential Equations Using R and INLA

Advanced Spatial Modeling with Stochastic Partial Differential Equations Using R and INLA

Elias Krainski; Virgilio Gómez-Rubio; Haakon Bakka; Amanda Lenzi; Daniela Castro-Camilo; Daniel Simpson; Finn Lindgren; Håvard Rue

CRC Press
2018
sidottu
Modeling spatial and spatio-temporal continuous processes is an important and challenging problem in spatial statistics. Advanced Spatial Modeling with Stochastic Partial Differential Equations Using R and INLA describes in detail the stochastic partial differential equations (SPDE) approach for modeling continuous spatial processes with a Matérn covariance, which has been implemented using the integrated nested Laplace approximation (INLA) in the R-INLA package. Key concepts about modeling spatial processes and the SPDE approach are explained with examples using simulated data and real applications.This book has been authored by leading experts in spatial statistics, including the main developers of the INLA and SPDE methodologies and the R-INLA package. It also includes a wide range of applications:* Spatial and spatio-temporal models for continuous outcomes* Analysis of spatial and spatio-temporal point patterns* Coregionalization spatial and spatio-temporal models* Measurement error spatial models* Modeling preferential sampling* Spatial and spatio-temporal models with physical barriers* Survival analysis with spatial effects* Dynamic space-time regression* Spatial and spatio-temporal models for extremes* Hurdle models with spatial effects* Penalized Complexity priors for spatial modelsAll the examples in the book are fully reproducible. Further information about this book, as well as the R code and datasets used, is available from the book website at http://www.r-inla.org/spde-book.The tools described in this book will be useful to researchers in many fields such as biostatistics, spatial statistics, environmental sciences, epidemiology, ecology and others. Graduate and Ph.D. students will also find this book and associated files a valuable resource to learn INLA and the SPDE approach for spatial modeling.
The International Judge

The International Judge

Daniel Terris; Cesare P.R. Romano; Leigh Swigart

Oxford University Press
2007
sidottu
Over the last century, international courts, once reserved for arcane matters of diplomacy and trade, have begun to address a broad range of human experience and activity. This volume corrects some of the common misperceptions about international judges, while providing a balanced introduction to both the strengths and shortcomings of their work. As they rule on crucial issues of war and peace, human rights, and trade, in addition to high-profile criminal trials, international judges are playing a critical role in developments that will affect world affairs for years to come. Based on interviews with more than 30 international judges, this volume is the first comprehensive portrait of the men and women in this new global profession. The working environment of international judges is closely examined in courts around the world, highlighting the challenge of carrying out work in multiple languages, in the context of intricate bureaucratic hierarchies, and with a necessary interdependence between judges and their courts' administration. Arguing that international judges have to balance their responsibilities as interpreters of the law and as global professionals, the authors discuss the challenges of working in the fluid circumstances of international courts. Profiles of five individual judges provide insight into the experience and dilemmas of the men and women on the international bench.
The City and the Hospital

The City and the Hospital

Daniel Skinner; Jonathan R. Wynn; Berkeley Franz

THE UNIVERSITY OF CHICAGO PRESS
2023
sidottu
A surprising look at how hospitals affect and are affected by their surrounding communities. An enduring paradox of urban public health is that many communities around hospitals are economically distressed and, counterintuitively, medically underserved. In The City and the Hospital two sociologists, Jonathan R. Wynn and Berkeley Franz, and a political scientist, Daniel Skinner, track the multiple causes of this problem and offer policy solutions. Focusing on three urban hospitals—Connecticut’s Hartford Hospital, the flagship of the Hartford Healthcare system; the Cleveland Clinic, which coordinates with other providers for routine care while its main campus provides specialty care; and the University of Colorado Hospital, a rare example of an urban institution that relocated to a new community—the authors analyze the complicated relationship between a hospital and its neighborhoods. On the one hand, hospitals anchor the communities that surround them, often staying in a neighborhood for decades. Hospitals also craft strategies to engage with the surrounding community, many of those focused on buying locally and hiring staff from their surrounding area. On the other hand, hospitals will often only provide care to the neighboring community through emergency departments, reserving advanced medical care and long-term treatment for those who can pay a premium for it. In addition, the authors show, hospitals frequently buy neighborhood real estate and advocate for development programs that drive gentrification and displacement. To understand how urban healthcare institutions work with their communities, the authors address power, history, race, and urbanity as much as the workings of the medical industry. These varied initiatives and effects mean that understanding urban hospitals requires seeing them in a new light—not only as medical centers but as complicated urban forces.
The City and the Hospital

The City and the Hospital

Daniel Skinner; Jonathan R. Wynn; Berkeley Franz

THE UNIVERSITY OF CHICAGO PRESS
2023
nidottu
A surprising look at how hospitals affect and are affected by their surrounding communities. An enduring paradox of urban public health is that many communities around hospitals are economically distressed and, counterintuitively, medically underserved. In The City and the Hospital two sociologists, Jonathan R. Wynn and Berkeley Franz, and a political scientist, Daniel Skinner, track the multiple causes of this problem and offer policy solutions. Focusing on three urban hospitals—Connecticut’s Hartford Hospital, the flagship of the Hartford Healthcare system; the Cleveland Clinic, which coordinates with other providers for routine care while its main campus provides specialty care; and the University of Colorado Hospital, a rare example of an urban institution that relocated to a new community—the authors analyze the complicated relationship between a hospital and its neighborhoods. On the one hand, hospitals anchor the communities that surround them, often staying in a neighborhood for decades. Hospitals also craft strategies to engage with the surrounding community, many of those focused on buying locally and hiring staff from their surrounding area. On the other hand, hospitals will often only provide care to the neighboring community through emergency departments, reserving advanced medical care and long-term treatment for those who can pay a premium for it. In addition, the authors show, hospitals frequently buy neighborhood real estate and advocate for development programs that drive gentrification and displacement. To understand how urban healthcare institutions work with their communities, the authors address power, history, race, and urbanity as much as the workings of the medical industry. These varied initiatives and effects mean that understanding urban hospitals requires seeing them in a new light—not only as medical centers but as complicated urban forces.
Abominable Science!

Abominable Science!

Daniel Loxton; Donald R. Prothero; Michael Shermer

Columbia University Press
2013
sidottu
Throughout our history, humans have been captivated by mythic beasts and legendary creatures. Tales of Bigfoot, the Yeti, and the Loch Ness monster are part of our collective experience. Now comes a book from two dedicated investigators that explores and elucidates the fascinating world of cryptozoology. Daniel Loxton and Donald R. Prothero have written an entertaining, educational, and definitive text on cryptids, presenting the arguments both for and against their existence and systematically challenging the pseudoscience that perpetuates their myths. After examining the nature of science and pseudoscience and their relation to cryptozoology, Loxton and Prothero take on Bigfoot; the Yeti, or Abominable Snowman, and its cross-cultural incarnations; the Loch Ness monster and its highly publicized sightings; the evolution of the Great Sea Serpent; and Mokele Mbembe, or the Congo dinosaur. They conclude with an analysis of the psychology behind the persistent belief in paranormal phenomena, identifying the major players in cryptozoology, discussing the character of its subculture, and considering the challenge it poses to clear and critical thinking in our increasingly complex world.