Question

34. Types of probability distributions by taking their functions of considerations must iäcluded
(A) posterior probability distribution
{B) discrete probability distribution
(C) continuous probability distribution

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Answer 1

Answer:

a

Step-by-step explanation:

refer to attachment

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Answer 2

A) Use of posterior probabilities in decision making

What Is a Posterior Probability? A posterior probability, in Bayesian statistics, is the revised or updated probability of an event occurring after taking into consideration new information. The posterior probability is calculated by updating the prior probability using Bayes' theorem.

B) A discrete probability function is a function that can take a discrete number of values (not necessarily finite). This is most often the non-negative integers or some subset of the non-negative integers. ... Each of the discrete values has a certain probability of occurrence that is between zero and one.

C) A continuous probability density function and the probability that the outcome lies in the interval a ≤ x ≤ b. p ( x lies between a and b ) = ∫ a b f ( x ) d x . The cumulative distribution function gives us the probability of this value or any previous value (it is like the cumulative relative frequency).