R companion to elementary applied statistics / Christopher Hay-Jahans.Call number: QA276.45.R3 H39 2019 Material type: TextPublisher: Boca Raton : CRC Press, Taylor & Francis Group, 2019Description: xvii, 358 pages : illustrations, charts ; 24 cm.Content type: text | still image Media type: unmediated Carrier type: volumeISBN: 9781138329164 (pbk.)Other title: Companion to elementary applied statistics.Subject(s): Statistics -- Data processing | R (Computer program language)DDC classification: 519.50285/5133
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Includes bibliographical references and index.
Preliminaries -- Bringing data into and out of R -- Accessing contents of data structures -- Altering and manipulating data -- Summaries and statistics -- More on computing with R -- Basic charts for categorical data -- Basic plots for numeric data -- Scatterplots, lines, and curves -- More graphics tools -- Test for one and two proportions -- Tests for more than two proportions -- Tests of variances and spread -- Tests for one or two means -- Tests for more than two means -- Selected tests for medians and more -- Dependence and independence.
The R Companion to Elementary Applied Statistics includes traditional applications covered in elementary statistics courses as well as some additional methods that address questions that might arise during or after the application of commonly used methods. Beginning with basic tasks and computations with R, readers are then guided through ways to bring data into R, manipulate the data as needed, perform common statistical computations and elementary exploratory data analysis tasks, prepare customized graphics, and take advantage of R for a wide range of methods that find use in many elementary applications of statistics. Features: Requires no familiarity with R or programming to begin using this book. Can be used as a resource for a project-based elementary applied statistics course, or for researchers and professionals who wish to delve more deeply into R. Contains an extensive array of examples that illustrate ideas on various ways to use pre-packaged routines, as well as on developing individualized code. Presents quite a few methods that may be considered non-traditional, or advanced. Includes accompanying carefully documented script files that contain code for all examples presented, and more. R is a powerful and free product that is gaining popularity across the scientific community in both the professional and academic arenas. Statistical methods discussed in this book are used to introduce the fundamentals of using R functions and provide ideas for developing further skills in writing R code. These ideas are illustrated through an extensive collection of examples.