This course is an introduction to statistical thinking and basic data analysis as practiced in the biological sciences. We will start with foundational topics in data types, descriptive statistics and data visualization, simple and conditional probability, random variables and distributions, and how we make inferences about groups from relatively small samples. That material will prepare us to move to topics in statistical inference and hypothesis testing, including topics that you may have been exposed to previously, like t-tests and analysis of variance (ANOVA). Throughout all of this, we’ll spend a significant amount of time getting comfortable using the R computing environment, for example writing commands and simple programs ("coding") to automate analytical tasks. R is a free software environment for statistical computing and programming and is among the most popular programming environments for data visualization and analysis.
- Teacher: Nicole Baran