The mode of these distributions can be approximated using MAP estimates. For 10 points each:
[10m] Name these updated distributions generated after considering observed data. In Bayesian inference, these distributions are proportional to the product of the likelihood and the prior distribution.
ANSWER: posterior distribution [or posterior probability]
[10e] Posterior probabilities are these kinds of probabilities that are calculated using Bayes’s theorem. For events A and B, this is the probability of event A occurring given that event B occurred.
ANSWER: conditional probability
[10h] These intervals are generated from the CDFs of posterior distributions. Confidence intervals are frequentist analogs to these intervals, which map where an unobserved parameter may fall at a certain probability.
ANSWER: credible intervals [reject “prediction intervals”]
<Science - Other Science>