| 书目名称 | Introductory Applied Statistics | | 副标题 | With Resampling Meth | | 编辑 | Bruce Blaine | | 视频video | | | 概述 | Includes data analytic examples in R.Provides problems at the end of each chapter for practice or assessment.Features accompanying tutorial-style video lectures as instructional supplements | | 图书封面 |  | | 描述 | This book offers an introduction to applied statistics through data analysis, integrating statistical computing methods. It covers robust and non-robust descriptive statistics used in each of four bivariate statistical models that are commonly used in research: ANOVA, proportions, regression, and logistic. The text teaches statistical inference principles using resampling methods (such as randomization and bootstrapping), covering methods for hypothesis testing and parameter estimation. These methods are applied to each statistical model introduced in preceding chapters..Data analytic examples are used to teach statistical concepts throughout, and students are introduced to the R packages and functions required for basic data analysis in each of the four models. The text also includes introductory guidance to the fundamentals of data wrangling, as well as examples of write-ups so that students can learn how to communicate findings. Each chapter includes problems forpractice or assessment. Supplemental instructional videos are also available as an additional aid to instructors, or as a general resource to students. .This book is intended for an introductory or basic statistics cours | | 出版日期 | Textbook 2023 | | 关键词 | Data Science; Data Analytics; Stochastic Modelling in Statistics; applied statistics; John Tukey; basic s | | 版次 | 1 | | doi | https://doi.org/10.1007/978-3-031-27741-2 | | isbn_softcover | 978-3-031-27743-6 | | isbn_ebook | 978-3-031-27741-2 | | copyright | The Editor(s) (if applicable) and The Author(s), under exclusive license to Springer Nature Switzerl |
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发表于 2025-3-21 16:53:03
