Matt reveals why AB Testing – and analytics more generally – is all about uncertainty. Understanding the causal inference problem is key, as well as getting a firm hold on reasoning, the importance of assignment, and the logic of p-values. Matt covers analytics as inference, walks through step by step how to calculate the variance (so there are formulas), and shines a light on sampling distribution (Central Limit Theorem). Learn what is required to move from statistical inference to causal inference and AB Testing. This session is statistically significant.