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easy
Bayesian Statistics
In Bayesian inference, before observing any data, you believe a coin has a 70% chance of being fair (P(fair) = 0.70). This belief is called what, and how does it interact with observed data?
A
The posterior — it is updated after data collection
B
The likelihood — it measures how probable the data is under each hypothesis
C
The prior — it encodes belief before seeing data and is updated via Bayes' theorem
D
The marginal — it represents the unconditional probability of the hypothesis
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