Project-Based R Companion to Introductory Statistics A Project-Based Approach using R

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.

Author

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.

1. Getting Started with R and RStudio
2. Describing Categorical Data
3. Describing Quantitative Data
4. The Normal Distribution
5. Two-Way Tables
6. Linear Regression and Correlation
7. Random Sampling
8. Inference About a Population Mean
9. Inference About a Population Proportion
10. Comparing Two Population Means
11. Comparing Two Population Proportions
12. Student Project 1
13. Student Project 2
14. Student Project 3

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. She lives in Winter Park, Florida with her family.