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Can You Trust Large Uplifts in Your Test Results?

By: Deborah O'Malley, M.Sc. & Ishan Goel | Last updated February, 2024


In this informative 50-minute video interview, Associate Director of Data Science Ishan Goel of the top testing platform, VWO, answers the key question: can you trust large uplifts in your test results?

Ishan discusses what constitutes a trustworthy test result, based on statistical significance and sample size requirements.

You'll learn from him:

  • How confidence intervals impact trustworthy test results. Hint: as more samples are gathered, the confidence intervals become smaller and your data becomes more trustworthy.
  • The difference between the sample mean (standard error) and the population mean and why these terms matter to determine sample size requirements.
  • Why you don't necessarily need large sample sizes to get trustworthy test results, as long as the outcome is statistically significant.
  • What "Twyman's Law" is, why it's important to know, and how you can apply it to judge whether your own test results are trustworthy.
  • The importance of evaluating your test results based on past history, data segmentation, and consistency.

Ishan offers a wealth of knowledge and actionable insights.

Listen and learn from one of the foremost data science experts in the field.

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