Question
X is a random variable taking values 0 and 1 with respective probabilities q and p. A sample X1 , X2 ,...., Xn of size n is taken from the distribution.If , shows that the bias of the estimator tends to zero as n tends to infinity.
Answer :
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Skip in 10
To solve this numerically, let's first set up the problem mathematically: Let \( X \) be a random variable taking values 0 and 1 with probabilities \( q \) and \( p \), respectively. So, the probability distribution of \( X \) is: \[ P(X = 1) = p \quad \text{and} \quad P(X = 0) = q = 1 - p \] Now, we have a sample of size \( n \), denoted by \( X_1, X_2, ..., X_n \), taken from this distribution. We want to consider the sum of these random variables: \[ S_n = \sum_{i=1}^{n} X_i \] This sum represents the total number of successes in \( n \) trials. Each \( X_i \) is an independent Bernoulli random variable with success probability \( p \). The expectation of the sum \( S_n \) is given by: \[
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