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Ten Projects in Applied Statistics

Ten Projects in Applied Statistics PDF Author: Peter McCullagh
Publisher: Springer Nature
ISBN: 3031142756
Category : Mathematics
Languages : en
Pages : 415

Book Description
The first half of the book is aimed at quantitative research workers in biology, medicine, ecology and genetics. The book as a whole is aimed at graduate students in statistics, biostatistics, and other quantitative disciplines. Ten detailed examples show how the author approaches real-world statistical problems in a principled way that allows for adequate compromise and flexibility. The need to accommodate correlations associated with space, time and other relationships is a recurring theme, so variance-components models feature prominently. Statistical pitfalls are illustrated via examples taken from the recent scientific literature. Chapter 11 sets the scene, not just for the second half of the book, but for the book as a whole. It begins by defining fundamental concepts such as baseline, observational unit, experimental unit, covariates and relationships, randomization, treatment assignment, and the role that these play in model formulation. Compatibility of the model with the randomization scheme is crucial. The effect of treatment is invariably modelled as a group action on probability distributions. Technical matters connected with space-time covariance functions, residual likelihood, likelihood ratios, and transformations are discussed in later chapters.

Ten Projects in Applied Statistics

Ten Projects in Applied Statistics PDF Author: Peter McCullagh
Publisher: Springer Nature
ISBN: 3031142756
Category : Mathematics
Languages : en
Pages : 415

Book Description
The first half of the book is aimed at quantitative research workers in biology, medicine, ecology and genetics. The book as a whole is aimed at graduate students in statistics, biostatistics, and other quantitative disciplines. Ten detailed examples show how the author approaches real-world statistical problems in a principled way that allows for adequate compromise and flexibility. The need to accommodate correlations associated with space, time and other relationships is a recurring theme, so variance-components models feature prominently. Statistical pitfalls are illustrated via examples taken from the recent scientific literature. Chapter 11 sets the scene, not just for the second half of the book, but for the book as a whole. It begins by defining fundamental concepts such as baseline, observational unit, experimental unit, covariates and relationships, randomization, treatment assignment, and the role that these play in model formulation. Compatibility of the model with the randomization scheme is crucial. The effect of treatment is invariably modelled as a group action on probability distributions. Technical matters connected with space-time covariance functions, residual likelihood, likelihood ratios, and transformations are discussed in later chapters.

Ten Projects in Applied Statistics

Ten Projects in Applied Statistics PDF Author: Peter McCullagh
Publisher:
ISBN: 9783031142765
Category :
Languages : en
Pages : 0

Book Description
The first half of the book is aimed at quantitative research workers in biology, medicine, ecology and genetics. The book as a whole is aimed at graduate students in statistics, biostatistics, and other quantitative disciplines. Ten detailed examples show how the author approaches real-world statistical problems in a principled way that allows for adequate compromise and flexibility. The need to accommodate correlations associated with space, time and other relationships is a recurring theme, so variance-components models feature prominently. Statistical pitfalls are illustrated via examples taken from the recent scientific literature. Chapter 11 sets the scene, not just for the second half of the book, but for the book as a whole. It begins by defining fundamental concepts such as baseline, observational unit, experimental unit, covariates and relationships, randomization, treatment assignment, and the role that these play in model formulation. Compatibility of the model with the randomization scheme is crucial. The effect of treatment is invariably modelled as a group action on probability distributions. Technical matters connected with space-time covariance functions, residual likelihood, likelihood ratios, and transformations are discussed in later chapters.

Statistics for Public Administration

Statistics for Public Administration PDF Author: Maureen Berner
Publisher: International City/County Management Association(ICMA)
ISBN: 9780873267717
Category : Business & Economics
Languages : en
Pages : 176

Book Description


A Modern Introduction to Probability and Statistics

A Modern Introduction to Probability and Statistics PDF Author: F.M. Dekking
Publisher: Springer Science & Business Media
ISBN: 1846281687
Category : Mathematics
Languages : en
Pages : 485

Book Description
Suitable for self study Use real examples and real data sets that will be familiar to the audience Introduction to the bootstrap is included – this is a modern method missing in many other books

Using R for Introductory Statistics

Using R for Introductory Statistics PDF Author: John Verzani
Publisher: CRC Press
ISBN: 1315360306
Category : Computers
Languages : en
Pages : 522

Book Description
The second edition of a bestselling textbook, Using R for Introductory Statistics guides students through the basics of R, helping them overcome the sometimes steep learning curve. The author does this by breaking the material down into small, task-oriented steps. The second edition maintains the features that made the first edition so popular, while updating data, examples, and changes to R in line with the current version. See What’s New in the Second Edition: Increased emphasis on more idiomatic R provides a grounding in the functionality of base R. Discussions of the use of RStudio helps new R users avoid as many pitfalls as possible. Use of knitr package makes code easier to read and therefore easier to reason about. Additional information on computer-intensive approaches motivates the traditional approach. Updated examples and data make the information current and topical. The book has an accompanying package, UsingR, available from CRAN, R’s repository of user-contributed packages. The package contains the data sets mentioned in the text (data(package="UsingR")), answers to selected problems (answers()), a few demonstrations (demo()), the errata (errata()), and sample code from the text. The topics of this text line up closely with traditional teaching progression; however, the book also highlights computer-intensive approaches to motivate the more traditional approach. The authors emphasize realistic data and examples and rely on visualization techniques to gather insight. They introduce statistics and R seamlessly, giving students the tools they need to use R and the information they need to navigate the sometimes complex world of statistical computing.

Community-Based Research

Community-Based Research PDF Author: Mary Beckman
Publisher: Taylor & Francis
ISBN: 1000974782
Category : Education
Languages : en
Pages : 367

Book Description
Community-based research (CBR) refers to collaborative investigation by academics and non-academic community members that fosters positive change on a local level. Despite recent trends toward engaged scholarship, few publications demonstrate how to effectively integrate CBR into academic course work or take advantage of its potential for achieving community change. Community-Based Research: Teaching for Community Impact fills these gaps by providing: * An overview of language and methods used by professionals engaged in CBR* A framework for orienting CBR toward concrete community outcomes* Effective ways to integrate CBR into course content, student-driven projects, and initiatives spanning disciplines, curricula, campuses and countries* Lessons learned in working toward positive outcomes for students and in communitiesThis text is designed for faculty, graduate students, service-learning and other engaged learning and scholarship practitioners, alliance members, special interest groups, and organizations that desire to strengthen student learning and utilize research for improvement in their communities.

OpenIntro Statistics

OpenIntro Statistics PDF Author: David Diez
Publisher:
ISBN: 9781943450046
Category :
Languages : en
Pages :

Book Description
The OpenIntro project was founded in 2009 to improve the quality and availability of education by producing exceptional books and teaching tools that are free to use and easy to modify. We feature real data whenever possible, and files for the entire textbook are freely available at openintro.org. Visit our website, openintro.org. We provide free videos, statistical software labs, lecture slides, course management tools, and many other helpful resources.

From Big Data to Intelligent Data

From Big Data to Intelligent Data PDF Author: Fady A. Harfoush
Publisher: Springer Nature
ISBN: 3030769909
Category : Business & Economics
Languages : en
Pages : 121

Book Description
This book addresses many of the gaps in how industry and academia are currently tackling problems associated with big data. It introduces novel concepts, describes the end-to-end process, and connects the various pieces of the puzzle to offer a holistic view. In addition, it explains important concepts for a wide audience, using accessible language, diagrams, examples and analogies to do so. The book is intended for readers working in industry who want to expand their knowledge or pursue a related degree, and employs an industry-centered perspective.

Foreign operations, export financing, and related programs appropriations for 1989

Foreign operations, export financing, and related programs appropriations for 1989 PDF Author: United States. Congress. House. Committee on Appropriations. Subcommittee on Foreign Operations, Export Financing, and Related Programs
Publisher:
ISBN:
Category : Economic assistance, American
Languages : en
Pages : 1488

Book Description


Statistical Foundations, Reasoning and Inference

Statistical Foundations, Reasoning and Inference PDF Author: Göran Kauermann
Publisher: Springer Nature
ISBN: 3030698270
Category : Mathematics
Languages : en
Pages : 361

Book Description
This textbook provides a comprehensive introduction to statistical principles, concepts and methods that are essential in modern statistics and data science. The topics covered include likelihood-based inference, Bayesian statistics, regression, statistical tests and the quantification of uncertainty. Moreover, the book addresses statistical ideas that are useful in modern data analytics, including bootstrapping, modeling of multivariate distributions, missing data analysis, causality as well as principles of experimental design. The textbook includes sufficient material for a two-semester course and is intended for master’s students in data science, statistics and computer science with a rudimentary grasp of probability theory. It will also be useful for data science practitioners who want to strengthen their statistics skills.