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Joint, Marginal, and Conditional

Joint, Marginal, and Conditional

作者: 宣雄民 | 来源:发表于2021-08-13 21:44 被阅读0次

Joint, Marginal, and Conditional Probabilities


Joint Probability

  • Intersectiion

It occurs whenever event A and event B both occur

  • Joint Probability

The probability that the intersection of two events occurs

  • "A and B", A \cap B
  • Example

Marginal probability

  • Marginal probability

The probability that an individual event from one experiment occurs, regardless of the outcomes from another experiment

  • Example


Conditional probability

  • Conditional probability

When one event occurs, it may impact the probability of an event from a different experiment

  • Definition

The probability that a second event(B) will occur given that we know that the first event(A) has already occurred

  • A and B come from two different experiments
    P(B|A) \rightarrow vertical bar "|" means "given"

  • Formula
    P(B|A) = \frac{P(A\cap B)}{P(A)}
    B \rightarrow Event we want the probability for
    A \rightarrow Event that has already occurred

    • Find the joint probability of A and B
    • Find the marginal probability of the event that has already occurred(Event A)
    • Divide te joint probability by the marginal probability

Main take away

  • Joint probability indicates the intersection portion, which both event A and event B occur at the same
  • Marginal probability represents the probability of one event reguardless the outcomes from other events
  • Conditional probability yields the probability of event B with reguard the event A has already happened.

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