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i=1 Example: In the case of tossing a coin twice, the random variable X represents the number of heads obtained the probability distribution of the discrete random variable? Solution:

i=1 Example: In the case of tossing a coin twice, the random variable X represents the number of heads obtained the probability distribution of the discrete random variable? Solution:

MATLAB: An Introduction with Applications
MATLAB: An Introduction with Applications
6th Edition
ISBN:9781119256830
Author:Amos Gilat
Publisher:Amos Gilat
Chapter1: Starting With Matlab
Section: Chapter Questions
Problem 1P
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● ber of possible values of X is finite or countably infinite, X is a discrete variable, i.e. the possible values of X may be listed as X₁, X2, ..., Xn- With each possible outcome x,, we associate a number: - p(x) = P(X= x;), p(x) must satisfy p(x;) ≥ 0 Σp(x)=L i=1 Solution: where p is the probability function. Vi (for all i) Example: In the case of tossing a coin twice, the random variable X represents the number of heads obtained. the probability distribution of the discrete random variable?
Transcribed Image Text:● ber of possible values of X is finite or countably infinite, X is a discrete variable, i.e. the possible values of X may be listed as X₁, X2, ..., Xn- With each possible outcome x,, we associate a number: - p(x) = P(X= x;), p(x) must satisfy p(x;) ≥ 0 Σp(x)=L i=1 Solution: where p is the probability function. Vi (for all i) Example: In the case of tossing a coin twice, the random variable X represents the number of heads obtained. the probability distribution of the discrete random variable?
↑ where X id n! x!(n-x)! = np. Expectation and Variance of a Binomial Random Variable E(X)=Σxp(x) XES V(X)=E(X-µ)² =np(1-p). m (a) exactly 2 are defective (b) at least 2 are defective (c) at most 2 are defective. *O The Binomial Distribution Example: 10% of a certain manufacturers flares are defective. If a random sample of twelve are fired, find the probability that What is the mean and variance?
Transcribed Image Text:↑ where X id n! x!(n-x)! = np. Expectation and Variance of a Binomial Random Variable E(X)=Σxp(x) XES V(X)=E(X-µ)² =np(1-p). m (a) exactly 2 are defective (b) at least 2 are defective (c) at most 2 are defective. *O The Binomial Distribution Example: 10% of a certain manufacturers flares are defective. If a random sample of twelve are fired, find the probability that What is the mean and variance?
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