what is the difference between joint and conditional probability?
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Joint probability is a measure of how likely it is that two (or more) things will both occur. ... Conditional probability is a measure of how likely one thing is to happen if you know that another thing has happened.
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As you probably already know, “if” is conditional. It is used to describe a possible situation, and what would happen under the conditions of that situation. “Unless” is also conditional, but it is effectively “if” with an extra exclusion or negative qualifier added. Unless basically means “except if” or “if… not”.
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The probability of the events are said to be disjoint, meaning that they cannot interact, are strictly independent. If the probability of event A is mutually exclusive with event B, then the joint probability of event A and event B is zero.
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Likelihood is the probability that an event that has already occurred would yield a specific outcome. Probability refers to the occurrence of future events, while a likelihood refers to past events with known outcomes. Probability is used when describing a function of the outcome given a fixed parameter value.
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Likelihood is the hypothetical probability that an event that has already occurred would yield a specific outcome. The concept differs from that of a probability in that a probability refers to the occurrence of future events, while a likelihood refers to past events with known outcomes.
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Definitions and Notation Two events are mutually exclusive or disjoint if they cannot occur at the same time. The probability that Event A occurs, given that Event B has occurred, is called a conditional probability. ... If Events A and B are mutually exclusive, P(A ∩ B) = 0.
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Consider two discrete random variables X and Y. ... Intuitively, two random variables X and Y are independent if knowing the value of one of them does not change the probabilities for the other one. In other words, if X and Y are independent, we can write P(Y=y|X=x)=P(Y=y), for all x,y.
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Addition Rule 1: When two events, A and B, are mutually exclusive, the probability that A or B will occur is the sum of the probability of each event. Addition Rule 2: When two events, A and B, are non-mutually exclusive, there is some overlap between these events.
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If two events A and B are mutually exclusive, the events are called disjoint events. ... If the events A and B are not mutually exclusive, the probability is: (A or B) = p(A) + p(B) – p(A and B).
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Odds compare one event to another event, whereas probability compares one event to both possible events. Thus, when the odds are 1 to 2, the fraction for the Odds is 1/2, but the fraction to calculate the probability is 1/3. 1 to 2 odds is not the only odds we have the answer to.
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The main difference between a conditional <expression> and if-then-else statements in the C language is that the conditional is an expression!
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Mutually exclusive events are those that cannot happen simultaneously, whereas independent events are those whose probabilities do not affect one another.
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- P(A and B) = 0 if two events are mutually exclusive, then the probability of either occurring is the same of the probabilities of each occurring. - If two events are mutually exclusive, they cannot be independent and vice versa.
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In the case of two mutually exclusive events A and B, each of which has non-zero probability, we have that P(A)P(B)≠0, but P(A∩B)=0, so the events cannot be independent.
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Two events are mutually exclusive or disjoint if they cannot occur at the same time. The probability that Event A occurs, given that Event B has occurred, is called a conditional probability. ... If Events A and B are mutually exclusive, P(A ∩ B) = 0.
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There are two types of random variables, discrete and continuous.
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“Risk” refers to the probability of occurrence of an event or outcome. Statistically, risk = chance of the outcome of interest/all possible outcomes. ... “Odds” refers to the probability of occurrence of an event/probability of the event not occurring.