The article discusses the importance of running experiments in data science, particularly in the context of hiring nurses at IntelyCare during the pandemic. It illustrates a specific case where the company considered paying clinicians a $100 incentive to encourage them to complete their first shift but decided to conduct an experiment first. This decision was influenced by the need to understand the potential risks associated with the multiple comparisons problem, emphasizing validation of strategies before implementation in a rapidly changing environment.
Instead of offering an untested $100 incentive, we decided to run an experiment first, highlighting the importance of validating business decisions before implementation.
The multiple comparisons problem illustrates the risk of making decisions based on multiple tests without considering the significance of results, leading to false positives.
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