Although standard graduate statistics courses prepare students to design and run statistical analyses, courses generally do not spend a great deal of time discussing data management and workflows, which are critical to making research replicable, efficient, and accurate. This is unfortunate because the best designed statistical analysis is easily undone by poor data management, whether through misconstructed variables, unreplicable workflows, and/or poorly commented or documented workflows and programs. This course addresses this oversight by focusing on computational tools for data management and workflows, including using software packages such as Stata and python.
Data Types: Numerical, Categorical, Networks, Text
Methods: Data Management
Course Credits
3