Название: Statistics Using R: An Integrative ApproachАвтор: Sharon Lawner Weinberg, Daphna Harel, Sarah Knapp Abramowitz
Издательство: Cambridge University Press
Год: 2021
Страниц: 696
Язык: английский
Формат: pdf (true)
Размер: 15.1 MB
Using numerous examples with real data, this textbook closely integrates the learning of statistics with the learning of R. It is suitable for introductory-level learners, allows for curriculum flexibility, and includes, as an online resource, R-code script files for all examples and figures included in each chapter, for students to learn from and adapt and use in their future data analytic work. Other unique features created specifically for this textbook include an online R tutorial that introduces readers to data frames and other basic elements of the R architecture, and a CRAN library of datasets and functions that is used throughout the book. Essential topics often overlooked in other introductory texts, such as data management, are covered. The textbook includes online solutions to all end-of-chapter exercises and PowerPoint slides for all chapters as additional resources, and is suitable for those who do not have a strong background in mathematics.
To facilitate the analysis of data, and to provide students with a platform for actively engaging in the learning process associated with what it means to be a good researcher and data analyst, we incorporate the functionality of R version 3.5.3 into the presentation of statistical material using a highly integrative approach that reflects practice. Students learn R along with each new statistical method covered, thereby allowing them to apply their newly learned knowledge to the real world of applications. In addition to demonstrating the use of R within each chapter, all chapters have an associated .R file, that may be accessed from the textbook’s website along with other ancillary materials and resources. The .R files are designed to allow students not only to replicate all worked-out examples within a chapter, but also to reproduce the figures embedded in a chapter, and to create their own .R files by extracting and modifying commands from them. Emphasizing data workflow management throughout the text using the .R file allows students to begin to appreciate one of the key ingredients in being a good researcher.
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