p-value explained intuitively for CFA and FRM. Learn what a p-value really measures, common misinterpretations, decision rules, and exam traps in hypothesis testing.

Level of significance explained intuitively for CFA and FRM. Understand hypothesis testing, false positives, decision thresholds, and the trade-off with test power.

Power of a statistical test explained intuitively for CFA and FRM. Learn how power affects hypothesis testing, false negatives, and meaningful statistical conclusions.

Conditional independence explained with intuition and real finance examples. Learn how conditioning changes relationships in credit risk, factor models, fraud analytics, and why conditional independence matters for CFA and FRM exams.

Learn how to identify the right probability distribution for any problem. Understand key properties, relationships, and real-world applications of Normal, Binomial, Poisson, Beta, and other distributions.

Learn how to choose the right significance level (alpha) in hypothesis testing. Understand Type I and Type II errors, when to use smaller alphas, and how to balance statistical power and risk.