Suppose that we have a discrete random variable Xa with PDF and CDF fa(x) and Fa(x), and a continuous random variable X. with PDF and CDF f.(x) and F.(x). Now we create a new random variable X in the following way. We have a coin with P(H) = p. We toss the coin once. If it lands heads, then the value of X is determined according to the probability distribution of X4. If the coin lands tails, the value of X is determined according to the probability distribution of Xe. This is called Mixed Random Variable formulation. Find E[X²].
Suppose that we have a discrete random variable Xa with PDF and CDF fa(x) and Fa(x), and a continuous random variable X. with PDF and CDF f.(x) and F.(x). Now we create a new random variable X in the following way. We have a coin with P(H) = p. We toss the coin once. If it lands heads, then the value of X is determined according to the probability distribution of X4. If the coin lands tails, the value of X is determined according to the probability distribution of Xe. This is called Mixed Random Variable formulation. Find E[X²].
Holt Mcdougal Larson Pre-algebra: Student Edition 2012
1st Edition
ISBN:9780547587776
Author:HOLT MCDOUGAL
Publisher:HOLT MCDOUGAL
Chapter11: Data Analysis And Probability
Section11.8: Probabilities Of Disjoint And Overlapping Events
Problem 2C
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Binomial Distribution
Binomial is an algebraic expression of the sum or the difference of two terms. Before knowing about binomial distribution, we must know about the binomial theorem.
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