What if your A/B test needed 67 years to reach statistical significance? Sam found out the hard way. Join Sam and Shifra as they demystify statistical testing for the real world of data work, where the stakes are lower, the data is messier, and your stakeholders definitely do not know what a p-value is.

We talk about:

• P-values, null hypotheses, and why 0.05 was basically made up
• Type 1 and type 2 errors through the lens of job interviews
• When A/B testing actually makes sense (hint: you need more than 10 visitors a day)
• T-tests, chi-square, ANOVA, and F1 scores explained without the jargon
• Why a suspiciously high model accuracy is actually a red flag
• The difference between statistical significance and practical significance

Chapters:

0:00 - The 67-year A/B te ...