Explanation:
In Bayesian inference, P(A) is the prior probability, representing initial belief about hypothesis A before observing evidence B; P(A|B) is the updated posterior probability.
Explanation:
Paasche index = Σ(p₁q₁)/Σ(p₀q₁) × 100, using current period quantities (q₁) as weights, which may understate inflation due to substitution effects but reflects current consumption patterns.
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