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Questions and Answers
Which distribution describes the likelihood of an event to occur given the outcome of another event?
Which distribution describes the likelihood of an event to occur given the outcome of another event?
- Marginal distribution
- Joint distribution
- Conditional distribution (correct)
- Probability distribution
How many variables is the marginal distribution a function of?
How many variables is the marginal distribution a function of?
- 3
- 1 (correct)
- 2
- 0
Which distribution describes the likelihood of an event to occur, independent of others?
Which distribution describes the likelihood of an event to occur, independent of others?
- Probability distribution
- Joint distribution
- Marginal distribution (correct)
- Conditional distribution
Which distribution can be calculated starting from the joint probability distribution of several events?
Which distribution can be calculated starting from the joint probability distribution of several events?
How many variables is the conditional distribution a function of?
How many variables is the conditional distribution a function of?
Which one of these is true about the marginal distribution?
Which one of these is true about the marginal distribution?
Which one of these is true about the conditional distribution?
Which one of these is true about the conditional distribution?
What is the difference between the marginal and conditional distributions?
What is the difference between the marginal and conditional distributions?
How can the marginal probability be calculated?
How can the marginal probability be calculated?
How many variables is the conditional distribution a function of?
How many variables is the conditional distribution a function of?
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Study Notes
Probability Distributions Overview
- Conditional Distribution: Describes the likelihood of an event occurring given the outcome of another event, highlighting dependency.
- Marginal Distribution: A function of one variable, focusing on the probabilities of individual events without considering others.
- Independent Events: Likelihood of an event occurs is described by the Marginal Distribution, which operates independently of other variables.
Other Key Distributions
- Joint Probability Distribution: Can be used to calculate conditional distributions. It represents the probability of multiple events occurring simultaneously.
- Conditional Distribution Variables: A function of two variables—the event given the condition of another event.
Marginal vs Conditional Distribution
- Marginal Distribution Characteristics: Some facts include that it sums or integrates the probabilities of a joint distribution across other variables.
- Conditional Distribution Characteristics: It assesses probabilities with respect to specific conditions, thus changes with varying conditions or outcomes.
Calculation Methods
- Marginal Probability Calculation: Can be computed from a joint probability distribution by summing or integrating over the other variable(s).
- Conditional Distribution Variables: Functions of two variables, reflecting the dependency on the conditioning event.
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