This course covers the basic foundations of statistical methods. In contrast to traditional methods of teaching statistics based on analytical formulas and hand-calculations, we will initially emphasize simulation-based methods (randomization tests, bootstrapping) for analyzing data. Students will learn how to implement common statistical methods (e.g., one and two sample tests, interval estimation techniques, linear regression) in the R programming language, and gain experience analyzing real data from a variety of fields, with particular emphasis on biological examples and applications.