Welcome to AB+ Context, where we explore A/B testing best practices enhanced by large language models. Our guides help you design, run, and analyze A/B tests with greater confidence and statistical rigor.
In A/B testing, one of the most common questions is: "How long should your A/B test run?" Determining test duration requires knowing your metric's current level and variability (e.g., conversion rate or standard deviation), your Minimum Detectable Effect, and your desired statistical power.
Read moreNow that chat-based LLMs sit only a browser tab away, many people paste their experiment data into ChatGPT and ask, "Is this statistically significant?" The workflow feels easier than fishing around for an online A/B‑testing calculator, and the AI's lengthy answer can sound authoritative. Convenience and extra text, however, do not guarantee statistical rigor — or a reliable conclusion.
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