Wayne Tai Lee

I’m a statistician who believes statistical literacy will make the world a better place. My initial draw towards statistics was because it went beyond data literacy and gave me a way to interpret the inspiring yet often chaotic world of data with the discipline of mathematics. Now, I see it as a discipline that encourages people to see different stories in the same data, that teaches us to be disciplined about our own beliefs, and to realize that we’ll never have enough data.

On the work side, statistics has helped me helped me coordinate AB testing platforms, data quality initiatives, and digital transformations across job functions and industries. When applied outside of work, believing that “all models are wrong, but some are useful” takes the pressure off a lot of things but also makes one appreciate the robustness of our world.

My current goals are to increase the statistical literacy of the world. Reach out if you’re interested and we can have a chat :)

Teaching and Side Projects

I teach statistics courses with an applied focus. Applied work is not easier given real world problems are never easier than textbook problems. One is constantly making trade-offs as we learn more about the context, the data, and the people involved in the problem. Making intentional trade-offs, however, are the mark of a seasoned data scientist and classic statistical theory has many answers.

My teaching philosophy is actually heavily influenced by my dance background:

• We learn through imitation (I believe this is largely perfected in high school)
• We learn by contrasting: the old vs the new, the familiar vs the foreign, minority vs non-minority etc.
• We learn by trying to articulate our own ideas (this is the active part which STEM students tend to resist)

You can find a list of my courses that source material from several applied projects.

There are three statistical concepts that I would like to teach to the world:

• The humility to know not all problems are data problems
• The creativity to think of “what else” could explain the variability dataset
• The discipline to list out the data that could change your mind

I’m slowly compiling a statistics concept inventory overtime.

Thoughts & Writing

I have several thoughts around statistics, data science, dance, and life if you care to read about them:

• Dance Lessons for Data Scientists
• 3 Statistical Concepts to Save the World
• Model like a model
• What does “work on a real problem” mean for prospective data scientists?
• Data scientists - soft skills are too soft, learn how to build trust
• An attempt to (re?)define wokeness with statistics