When we want to address equity in data science, we often need to talk about power and we sometimes need to talk about money. It can be useful to think about an individual’s data like a raw resource, you could call it something cheesy like “Dataonium”. There’s a reason...
When it comes to data projects, one of the most powerful tools we use is what we call a Motivation Touchstone. It’s a document that you and your team can return to over and over for guidance when figuring out how to make effective and equitable decisions at...
We’ve said it before: When you need to know more than just a general average, you need an Equity Gap Score. An average tells you what happened and an Equity Gap Score tells you for who. Each piece of information needs the other to give meaning. If you have a...
Early in my career, I was working on a project using education data, and we were having a meeting with policymakers, school principals, and a team of researchers. When one of the principals asked a question about what assumptions were used in crafting one of the...
I want to talk to you about why you should stop saying “not statistically significant” based on sample size alone. The term “not statistically significant” should only be applied to a hypothesis, not a sample size, and even then it’s an...
