Probabilities derived only from information currently available before new data are called which?

Probabilities derived only from information currently available before new data are called which?

• A. Posterior probabilities
• B. Conditional probabilities
• C. Joint probabilities
• D. Prior probabilities

Answer: (D)

In Bayesian reasoning, the probability you assign before seeing any new data is called the prior probability. It reflects what is known or believed from existing information up to that point. The idea is to start with this baseline belief and then update it when new evidence arrives, producing the posterior probability. The other terms describe probabilities that involve data or relationships learned after observing evidence. A conditional probability is the chance of something given that another event has occurred. A joint probability is the probability of two events happening together. A posterior probability is the updated probability after incorporating new data. So the description “derived only from information currently available before new data” specifically points to the prior.

In Bayesian reasoning, the probability you assign before seeing any new data is called the prior probability. It reflects what is known or believed from existing information up to that point. The idea is to start with this baseline belief and then update it when new evidence arrives, producing the posterior probability.

The other terms describe probabilities that involve data or relationships learned after observing evidence. A conditional probability is the chance of something given that another event has occurred. A joint probability is the probability of two events happening together. A posterior probability is the updated probability after incorporating new data. So the description “derived only from information currently available before new data” specifically points to the prior.