From the course: 15 Mistakes to Avoid in Data Science

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Including your bias

Including your bias

From the course: 15 Mistakes to Avoid in Data Science

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Including your bias

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- As a data scientist, it's easy to sit alone behind your computer and think about the data from your own perspective, which may be biased. And it's important to work with the data sets that you have with the communities that they represent, with the people who have context around that data set. Because as a data scientist, as one person looking at a data set, you really only have a limited perspective. You can't assume you know everything about that data, unless you're talking to people who are intimately familiar with whatever the data set represents, or are part of the community of whatever that data set represents. And if you don't include that voice in your analysis, it's going to be biased. And that's just being a human being, being alone. We all have our biases, if we bring those into our analysis, we're doing a disservice to the people it represents.

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