Hi, I’m Heather Krause a mathematical statistician, data scientist and founder of Datassist. After many years collecting data, conducting analysis, and designing data communication material across the globe it became really clear to me that data is never neutral. And that much of what we consider to be an objective science with “best practices” is often simply one world view among many. This is true even in something that appear genuinely value-free like math.
Lessons Learned: Math is math, right? Two is always two. Except when it’s not.
Let’s say we’re doing some research in the education sector and we want to talk about how average class size affects outcomes. We study three classes. Take a look at the image below and calculate the average class size.
The average class size at this school depends entirely on who you ask.
Even though there is nothing challenging or complex about the math involved in this question, we still can’t count on objective data analysis. Why? Because the “correct” answer depends on your worldview. Let’s look more closely.
If we ask the students how many students are in a class, we get the following answers:
Now let’s ask the professors how many students are in a class.
The first professor reports one student. The second professor says there are two students in a class, and the Class Three professor says there are four students per class.
The average class size depends entirely on whose point of view you’re taking. That is, where you put the locus of power (or centre of power) in your analysis — on the professors or on the students.
How often do we automatically put the centre of power in a specific place and simply assume that it’s correct. (Not that it’s necessarily incorrect — but it’s not the only option.)
Let’s look at the math.
Both answers are technically correct. The math is sound. But how does that work? The answer to the question “what’s the average class size?” depends on whether you’re a teacher or a student. And that’s why objective data analysis isn’t really a thing — because there will always be assumptions you need to make, and making assumptions removes objectivity.
Hot Tip: Every time you do an analysis or a calculation with your data, take five minutes and ask yourself:
- Where have I put the center of power in this calculation?
- Whose perspective could change this calculation?
- Can I come up with an entirely different yet also correct answer?
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