Type I and Type II Errors: The Inevitable Errors in Optimization Experiments
Type I and type II errors happen when you erroneously spot winners in your experiments or fail to spot them. With both errors, you end up going with what appears to work or not. And not with the real results.
Misinterpreting test results doesn’t just result in misguided optimization efforts but can also derail your optimization program in the long-term.
Find out what these errors mean for your experiments.
