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Webinar

Fireside Chat: Evolution of Statistics and Experimentation with VWO’s Lead Data Scientist

29 July 2024 AM Eastern time
Speaker
Ishan Goel

Ishan Goel

Associate Director of Data Science, VWO

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Join us for an exclusive fireside chat with VWO’s leading data scientist – the brains behind the enhanced stats engine that enables you to configure multiple statistical parameters, such as Region of practical equivalence and statistical power, and take control of your experiments.

What’s in it for you?

→ Understand how the evolution of statistics impacts experimentation

Hear from VWO’s lead data scientist about the advancements in statistics that inspired our enhanced stats engine. Learn about the breakthroughs that shaped our stats engine enhancements and how they benefit your experimentation efforts.

→ A brief overview of what’s changed with VWO’s enhanced reports

Get greater control over statistical parameters and an overall improved reporting experience. Gain detailed insights into our new stats engine, designed to transform your experimentation process. Improved visuals provide a consolidated view of probability thresholds and expected improvements. Benefit from smarter decision-making with a statistical engine that recommends disabling underperforming variations, enabling faster results.

→ Unlock never-before flexibility to run experiments the way you want

Discover how to leverage the new controls for Minimum Detectable Effect (MDE), False Positive Rate (FPR), and Region of Practical Equivalence (ROPE) to achieve more accurate and faster results in the context of real-world experiments.

→ Interactive Q&A Session

Engage with our expert and get your questions answered in real-time. Learn how these enhancements can be applied to your specific use cases.

Some Questions You Can Expect:

  • Is there a loss between observed conversion improvement on campaigns and real-world conversions?
  • Where do you see the future of experimentation heading, and what role will advanced statistical controls play in that evolution?
  • What is the suitable trade-off between power and campaign resources? Does that mean my results will be incorrect?
  • Do you have any hygiene points or best practices to follow while running experiments?

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