Below are links to information useful for researchers working in my lab:
- Expectations of Graduate Students
- Writing in the Sciences, open source online course – highly recommended!
- Modest Advice for New Graduate Students by Dorsa Amir
- The US Government Accountability Office
- Reading Journal Articles in Levels Methodology (adopted from Russ Meller)
- Advice for Researchers and Students by Tao Xie.
- A list of 100 resources for Logistics
- Big O Notation for Algorithm Complexity
- The Limits of Quantum Computers, which provides a great description of complexity theory, and is an inspirational read about the interdisciplinary and human connections to complexity.
- Math 101: A reading list for lifelong learners
- Data Sets for Recommender Systems
- Data from Industry Partners via the Wharton Customer Analytics Initiative
- Get data off of websites quickly and without coding: Import.io
- Data Sets from an NYU Econometric Class
- Visualizations of Linear Algebra Youtube series
- Chester Ismay’s Awesome Inference Diagram for Statistical Analysis
- How to construct a research abstract
- Seeing Theory – A visual way to look at prob and stats
- OPL functions and IBM Knowledge Center
- R package to model MIPs
- GoogleDoc of The quartz directory of essential data sources
- R Resources