ECON10005 Chapter Notes - Chapter 3: Conditional Probability, Covariance, Conditional Variance
25 Aug 2018
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The distributions give the probability of each of the possible outcomes. If the random variable is denoted x then the discrete probability distribution is written ((cid:1850) = ) = () for any number x: using descriptive statistics for discrete random variable: A discrete random variable x with possible outcomes 1 + 2 + + and probability distribution () has expected value ((cid:1850)) = 1(1) + 2(2) + + () = () distribution () over possible outcomes = 1, 2, , . Suppose we have some random variable x with probability. If = (cid:1850)1 + (cid:1850)2 + + (cid:1850) ((cid:1850)) = ((cid:1850)1) + ((cid:1850)2) + + ((cid:1850)) Variance & standard deviation of random variable: Joint and marginal probability distribution: marginal probability: individual probabilities of a and b. Joint probability: the probability that both a and b occur. Independent random variables: 2 random variables x and y are independent (law of total probability) if:
