---
id: "prereq-ab-testing-stats"
type: "prereq"
source_timestamps: ["§ Controlled Experimentation"]
tags: ["data-science", "statistics"]
related: ["concept-controlled-experimentation-ai"]
reason: "Required to actually execute the 'Controlled Experimentation' discipline recommended by the authors."
sources: ["spine"]
sourceVaultSlug: "hbr-seg-spine"
originDay: 1
articleStem: "hbr-cl-95-6-disciplines-genai"
sourceUrl: "https://hbr.org/2024/07/the-6-disciplines-companies-need-to-get-the-most-out-of-gen-ai"
sourceTitle: "The 6 Disciplines Companies Need to Get the Most Out of Gen AI"
---
# A/B Testing and Statistical Significance

**Prerequisite knowledge:** the basics of experimental design (control vs. treatment groups) and how to determine whether results are statistically significant.

**Why it's required:** to actually execute the [[concept-controlled-experimentation-ai|Controlled Experimentation]] discipline — and the concrete step [[action-run-ai-experiments]] — the reader/organization must understand how to construct comparison groups and interpret significance. The authors note the statistics are straightforward for data scientists, but the capability must exist in-house.