Project-Based R Companion to Introductory Statistics 1st Edition

Resource-Based R Associate to Basic Statistics is conceived as a partner to a standard statistics or biostatistics textbook, with each section covering normal topics such as descriptive statistics, regression, and hypothesis testing. Nevertheless, in contrast to a standard textbook, every section will present its materials utilizing a thorough step-by-step analysis of an actual publicly available dataset, with an emphasis on the practical skills of testing assumptions, data exploration, and forming conclusions. The chapters in the primary body of the book contain an worked example displaying the R code utilized at each step followed by a multi-part project for college students to complete. These tasks, which may serve as alternatives to standard discrete homework problems, will illustrate how to “put the pieces together” and conduct a comprehensive start-to-finish data analysis using the R statistical software package. At the end of the book, there are several projects that necessitate the application of various statistical techniques which might be used as a take-home final examination or final project for a class.

Key features of the text:

• • Arranged 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, and many others.) so instructors can easily pair this supplementary material with course plans

• • Contains student projects for each chapter that can be assigned as laboratory exercises or homework assignments to complement typical homework

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

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

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

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