What’s selection bias? What other types of biases could you encounter during sampling?

When you’re dealing with a non-random sample, selection bias will occur due to flaws in the selection process. This happens when a subset of the data is consistently excluded because of a particular attribute. This exclusion will distort results and influence the statistical significance of the test.

Other types of biases include survivorship bias and undercoverage bias. It’s important to always consider and reduce such biases because you’ll want your smart algorithms to make accurate predictions based on the data.