STS 3300 STATISTICAL METHODS FOR DATA ANALYTICS
This course introduces students to best practices and advanced methods in statistics and data analytics. The goal of the course is not only to expand students’ repertoire of statistical techniques, but also to create responsible stewards of data and its analysis. This includes topics such as workflow, reproducibility, database management, missing data, data ethics, and statistical learning. Advanced statistical software such as SAS or R will be used. Emphasis will be placed on communicating methodology and results to both experts and the public through written and oral reports.
Course Types
Science
Offered
Winter and Fall of even years
Notes
- This course will prepare students in quantitative disciplines how to ethically navigate a world that produces copious amounts of data. Specific outcomes that should prove valuable include the ability to:
- Evaluate different software tools to improve personal workflow efficiency.
- Implement a plan for effective digital asset management and protection.
- Effectively plan, organize, and document quantitative analyses, especially when working in collaborations.
- Develop and implement robust and legible coding and computing strategies.
- Efficiently import, clean, manipulate, document, and export datasets from statistical software.
- Automate tasks in coding to reduce errors.
- Understand different types of missing data and strategies for how to handle them.
- Understand the Institutional Review Board process and its importance.
- Critically consider ethical data usage, storage, and analysis.
- Critically consider societal implications of data analysis procedures.