Bio5075 Introduction to Coding and Statistical Thinking for Genetics and Genomics

Work in the life sciences increasingly relies on large scale, quantitative data that requires basic computational and statistics skills. This course is an introduction to basic Python and statistical concepts used in molecular genetics and genomics, aimed at first-year DBBS students. The format emphasizes practical problem-solving skills by teaching both core statistical concepts, such as hypothesis testing, confidence intervals, bootstrap simulation, and power analysis, as well as computational methods to implement them. The goal of the course is to prepare students for more advanced coursework, as well as self-teaching during their research careers.