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Project-Based R Companion to Introductory Statistics: A Project-Based Approach using RНазвание: Project-Based R Companion to Introductory Statistics: A Project-Based Approach using R
Автор: Chelsea Myers
Издательство: CRC Press
Год: 2021
Страниц: 185
Язык: английский
Формат: pdf (true)
Размер: 10.1 MB

Project-Based R Companion to Introductory Statistics is envisioned as a companion to a traditional statistics or biostatistics textbook, with each chapter covering traditional topics such as descriptive statistics, regression, and hypothesis testing. However, unlike a traditional textbook, each chapter will present its material using a complete step-by-step analysis of a real publicly available dataset, with an emphasis on the practical skills of testing assumptions, data exploration, and forming conclusions. The chapters in the main body of the book include a worked example showing the R code used at each step followed by a multi-part project for students to complete. These projects, which could serve as alternatives to traditional discrete homework problems, will illustrate how to "put the pieces together" and conduct a complete start-to-finish data analysis using the R statistical software package. At the end of the book, there are several projects that require the use of multiple statistical techniques that could be used as a take-home final exam or final project for a class.

Key features of the text:

Organized in chapters focusing on the same topics found in typical introductory statistics textbooks (descriptive statistics, regression, two-way tables, hypothesis testing for means and proportions, etc.) so instructors can easily pair this supplementary material with course plans

Includes student projects for each chapter which can be assigned as laboratory exercises or homework assignments to supplement traditional homework

Features real-world datasets from scientific publications in the fields of history, pop culture, business, medicine, and forensics for students to analyze

Allows students to gain experience working through a variety of statistical analyses from start to finish

The book is written at the undergraduate level to be used in an introductory statistical methods course or subject-specific research methods course such as biostatistics or research methods for psychology or business analytics.

If you have any previous experience working with software that can do statistical analyses, it’s likely using Microsoft Excel. RStudio has many features that are point-and-click like Excel, but the commands used to run RStudio look a bit like lines of computer code, and that can be intimidating to some. However, we encourage you to put aside any preconceived notions about computer programming and instead focus on a different maxim: Working with RStudio isn’t harder than Excel (or another software you’ve used before), it’s just different.

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