Conditional probability is defined as
AP(A | B) = P(A ∩ B) / P(B), provided P(B) > 0
BP(A | B) = P(A) + P(B)
CP(A | B) = P(A) · P(B)
DP(A | B) = P(B | A) always
Answer & Solution
Correct answer: A. P(A | B) = P(A ∩ B) / P(B), provided P(B) > 0
P(A | B) = P(A ∩ B) / P(B). It is generally NOT symmetric in A and B (that's why Bayes's rule exists).
Related questions
The HESSIAN of a twice-differentiable scalar function f: ℝⁿ → ℝ isFor a Poisson(λ) random variable, the mean equals the variance and both equalEigenvalues λ of a square matrix A satisfyFor the standard NORMAL distribution N(0, 1), the mean and variance areBayes's rule allows you to computeA matrix A is INVERTIBLE if and only ifA Binomial(n, p) random variable has mean and varianceFor two independent random variables X and Y