Introductory Statistics 2e
Introductory Statistics 2e

Author: Barbara Illowsky

Publisher:

Published: 2023-12-13

Total Pages: 2106

ISBN-13:

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Introductory Statistics 2e provides an engaging, practical, and thorough overview of the core concepts and skills taught in most one-semester statistics courses. The text focuses on diverse applications from a variety of fields and societal contexts, including business, healthcare, sciences, sociology, political science, computing, and several others. The material supports students with conceptual narratives, detailed step-by-step examples, and a wealth of illustrations, as well as collaborative exercises, technology integration problems, and statistics labs. The text assumes some knowledge of intermediate algebra, and includes thousands of problems and exercises that offer instructors and students ample opportunity to explore and reinforce useful statistical skills. This is an adaptation of Introductory Statistics 2e by OpenStax. You can access the textbook as pdf for free at openstax.org. Minor editorial changes were made to ensure a better ebook reading experience. Textbook content produced by OpenStax is licensed under a Creative Commons Attribution 4.0 International License.

Importing Into the United States
Importing Into the United States

Author: U. S. Customs and Border Protection

Publisher:

Published: 2015-10-12

Total Pages: 0

ISBN-13: 9781304100061

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Explains process of importing goods into the U.S., including informed compliance, invoices, duty assessments, classification and value, marking requirements, etc.

The Algorithm Design Manual
The Algorithm Design Manual

Author: Steven S Skiena

Publisher: Springer Science & Business Media

Published: 2009-04-05

Total Pages: 742

ISBN-13: 1848000707

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This newly expanded and updated second edition of the best-selling classic continues to take the "mystery" out of designing algorithms, and analyzing their efficacy and efficiency. Expanding on the first edition, the book now serves as the primary textbook of choice for algorithm design courses while maintaining its status as the premier practical reference guide to algorithms for programmers, researchers, and students. The reader-friendly Algorithm Design Manual provides straightforward access to combinatorial algorithms technology, stressing design over analysis. The first part, Techniques, provides accessible instruction on methods for designing and analyzing computer algorithms. The second part, Resources, is intended for browsing and reference, and comprises the catalog of algorithmic resources, implementations and an extensive bibliography. NEW to the second edition: • Doubles the tutorial material and exercises over the first edition • Provides full online support for lecturers, and a completely updated and improved website component with lecture slides, audio and video • Contains a unique catalog identifying the 75 algorithmic problems that arise most often in practice, leading the reader down the right path to solve them • Includes several NEW "war stories" relating experiences from real-world applications • Provides up-to-date links leading to the very best algorithm implementations available in C, C++, and Java

Statistical Rethinking
Statistical Rethinking

Author: Richard McElreath

Publisher: CRC Press

Published: 2018-01-03

Total Pages: 488

ISBN-13: 1315362619

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Statistical Rethinking: A Bayesian Course with Examples in R and Stan builds readers’ knowledge of and confidence in statistical modeling. Reflecting the need for even minor programming in today’s model-based statistics, the book pushes readers to perform step-by-step calculations that are usually automated. This unique computational approach ensures that readers understand enough of the details to make reasonable choices and interpretations in their own modeling work. The text presents generalized linear multilevel models from a Bayesian perspective, relying on a simple logical interpretation of Bayesian probability and maximum entropy. It covers from the basics of regression to multilevel models. The author also discusses measurement error, missing data, and Gaussian process models for spatial and network autocorrelation. By using complete R code examples throughout, this book provides a practical foundation for performing statistical inference. Designed for both PhD students and seasoned professionals in the natural and social sciences, it prepares them for more advanced or specialized statistical modeling. Web Resource The book is accompanied by an R package (rethinking) that is available on the author’s website and GitHub. The two core functions (map and map2stan) of this package allow a variety of statistical models to be constructed from standard model formulas.

Dead Beat
Dead Beat

Author: Jim Butcher

Publisher: Penguin

Published: 2006-05-02

Total Pages: 530

ISBN-13: 1101128445

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“The wildest, strangest, best Dresden adventure to date...Butcher’s blending of modern fantasy with classic noir sensibilities ensures that there’s never a dull moment.”—SF Site Paranormal investigations are Harry Dresden’s business and Chicago is his beat, as he tries to bring law and order to a world of wizards and monsters that exists alongside everyday life. And though most inhabitants of the Windy City don’t believe in magic, the Special Investigations Department of the Chicago PD knows better. Karrin Murphy is the head of S. I. and Harry’s good friend. So when a killer vampire threatens to destroy Murphy’s reputation unless Harry does her bidding, he has no choice. The vampire wants the Word of Kemmler (whatever that is) and all the power that comes with it. Now, Harry is in a race against time—and six merciless necromancers—to find the Word before Chicago experiences a Halloween night to wake the dead...