Running faster tests: The basics (Part 1)

The text addresses the common challenge of needing to shorten the duration of experiments despite the lengthy timelines suggested by sample size calculators, a topic that will be explored in detail through a 4-part series. The series will examine various strategies, such as adjusting sample size calculator inputs, modifying primary metrics for quicker results, changing user targeting methods, and exploring different types of experiments to hasten completion. Key factors influencing experiment duration include traffic rate, minimum detectable effect (MDE), and error rates, each of which involves tradeoffs that can affect the accuracy and reliability of the experiment's results. The discussion emphasizes the need for careful consideration of these adjustments, as hasty changes can lead to increased risks of false positives and negatives, and ultimately, flawed decision-making. The text also foreshadows future posts in the series that will delve deeper into more nuanced adjustments for faster experiment runtimes.

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