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Experimentation Works: Statistical Concepts – Which ones are the most important in A/B testing?

Lisa Qian - Statistical Concepts: Which ones are the most important in A/B testing?

Talk – Statistical Concepts: Which ones are the most important in A/B testing?

Learn key statistical concepts to run a robust A/B test, from testing and correcting for bias in large scale experiments to maximizing statistical power when you have lower traffic.

Lisa Qian – Convoy

Lisa is a Senior Research Science Manager at Convoy. She leads experimentation, machine learning and analytics efforts on Marketplace Supply, which is responsible for network optimization and matching decisions.

Prior to joining Convoy, Lisa was a data science manager at Airbnb for over six years, leading data science teams across Search, Trust, and Customer Service.

She is an evangelist for driving product development using carefully designed and executed experiments, and has given numerous talks on the subject, including at Strata + Hadoop World, and is the author of the O’Reilly video “A/B testing, a Data Science Perspective”.

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