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single-variable case, we sa assigns nonzero probabiliti ay that the sum of the proE n the s to only a finite or cour

single-variable case, we sa assigns nonzero probabiliti ay that the sum of the proE n the s to only a finite or cour

Algebra and Trigonometry (MindTap Course List)
Algebra and Trigonometry (MindTap Course List)
4th Edition
ISBN:9781305071742
Author:James Stewart, Lothar Redlin, Saleem Watson
Publisher:James Stewart, Lothar Redlin, Saleem Watson
Chapter14: Counting And Probability
Section14.2: Probability
Problem 3E: The conditional probability of E given that F occurs is P(EF)=___________. So in rolling a die the...
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Question 1 1.1 In the single-variable case, we saw that the probability function for a discrete random variable Y assigns nonzero probabilities to a finite or countable number of distinct values of Y in such a way that the sum of the probabilities is equal to 1. Similarly, in the probabilities to only a finite or countable number of pairs of values. Further, the nonzero probabilities must sum to 1. case the joint probability function assigns nonzero 1.2 Describe in your own words, what the difference is between univariate and bivariate probability distributions. 1.3 In your own words, describe what is meant by two variables being independent 1.4 Probabilities may be either marginal, joint or conditional. Marginal probability may be thought of as an the 1.4.1 _probability. Joint probability is the probability of of two or more events. Conditional probability is the 1.4.2 probability of an event occurring, 1.4.3
Transcribed Image Text:Question 1 1.1 In the single-variable case, we saw that the probability function for a discrete random variable Y assigns nonzero probabilities to a finite or countable number of distinct values of Y in such a way that the sum of the probabilities is equal to 1. Similarly, in the probabilities to only a finite or countable number of pairs of values. Further, the nonzero probabilities must sum to 1. case the joint probability function assigns nonzero 1.2 Describe in your own words, what the difference is between univariate and bivariate probability distributions. 1.3 In your own words, describe what is meant by two variables being independent 1.4 Probabilities may be either marginal, joint or conditional. Marginal probability may be thought of as an the 1.4.1 _probability. Joint probability is the probability of of two or more events. Conditional probability is the 1.4.2 probability of an event occurring, 1.4.3
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