Project-Based R Companion to Introductory Statistics

<p><strong><em>Project-Based R Companion to Introductory Statistics</em></strong> 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.</p><p><strong>Key features of the text</strong>:</p><ul> <p> </p> <li>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</li> </ul><ul> <p> </p> <li>Includes student projects for each chapter which can be assigned as laboratory exercises or homework assignments to supplement traditional homework</li> </ul><ul> <p> </p> <li>Features real-world datasets from scientific publications in the fields of history pop culture business medicine and forensics for students to analyze</li> </ul><ul> <p> </p> <li>Allows students to gain experience working through a variety of statistical analyses from start to finish</li> </ul><p>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.</p><p><strong>Author</strong></p><p>After a 10-year career as a research biostatistician in the Department of Ophthalmology and Visual Sciences at the University of Wisconsin-Madison Chelsea Myers teaches statistics and biostatistics at Rollins College and Valencia College in Central Florida. She has authored or co-authored more than 30 scientific papers and presentations and is the creator of the MCAT preparation website MCATMath.com. </p>