Bernoulli Trials and Probability

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    Bernoulli Probability
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SUMMARY

The discussion centers on Bernoulli trials and their probability distributions, specifically focusing on a random variable X defined as the sum of 5 independent Bernoulli trials with a success probability r. The values of r are chosen from three possible options with specified probabilities. The joint probability distribution of X and R is computed, and the independence of Y and R is questioned, with Y not being explicitly defined in the context. The marginal distribution function of X, along with its unconditional mean and variance, is also explored.

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  • Understanding of Bernoulli trials and their properties
  • Familiarity with binomial distributions, specifically Binomial(5, r)
  • Knowledge of joint and marginal probability distributions
  • Proficiency in the law of total probability
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  • Study the law of total probability in depth
  • Learn about joint and marginal distributions in probability theory
  • Explore the concept of independence in random variables
  • Investigate the properties of binomial distributions and their applications
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Students of probability theory, statisticians, and anyone interested in understanding the behavior of random variables in the context of Bernoulli trials.

lucytranxx
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Let X be a random variable defined as the sum of 5 independent Bernoulli trials in which the probability of each Bernoulli taking the value 1 is given by r. Suppose that prior to the 5 Bernoulli trials, r is chosen to take one of three possible values with the following probabilities:
R=r P(R=r)
0.1 0.2
0.5 0.5
0.4 0.3

(a) Compute the joint probability distribution of X and R Are Y and R independent? Provide your reasoning.


(b) Compute the marginal distribution function of X and the unconditional mean and variance of Y

this was a question in one of the textbooks but i don't understand what X is suppose to be?
 
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In general, the sum of $n$ independent Bernoulli trials where the succes probability is $r$, follows a binomial distribution with parameters $n$ and $r$. Hence, $X \sim \mbox{Binomial}(5,r)$. Further, note that $X$ and $R$ are both discrete random variables. The (marginal) distribution of $R$ is given, however the distribution of $X$ depends on $R$. To find the distribution of $X$, you can make use of the law of total probability, that is,
$$\mathbb{P}(X=x) = \sum_{r} \mathbb{P}(X = x \ | \ R = r) \mathbb{P}(R = r)$$
where $x \in \{0,\ldots,n\}$.

Question: what is $Y$? I do not see any description.
 

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