Nerd Alert: The Statistical Significance Trap
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In this episode, Elena and Rob examine why treating statistical significance as proof can mislead marketers. They reveal how relying on a single P-value creates blind spots and why smart decisions require looking at the full picture of evidence.
Topics covered:
- [01:00] "Statistical Significance and Statistical Reporting, Moving Beyond Binary"
- [02:00] What statistical significance actually means
- [04:00] When significant results don't matter for business
- [05:00] Building a toolkit approach beyond P-values
- [06:00] Practical importance versus statistical significance
- [08:00] Avoiding single-test tunnel vision
To learn more, visit marketingarchitects.com/podcast or subscribe to our newsletter at marketingarchitects.com/newsletter.
Resources:
McShane, B. B., Bradlow, E. T., Lynch, J. G., Jr., & Meyer, R. J. (2024). “Statistical Significance” and statistical reporting: Moving beyond binary. Journal of Marketing, 88(1), 1–20.
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