Limit of probabilities of a large sample

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SUMMARY

The discussion centers on the convergence of the sample mean to the population mean as the sample size n approaches infinity, supported by the Central Limit Theorem. It is established that the sample mean distribution approximates a Normal distribution with parameters $$\mu = 2$$ and $$\sigma = \sqrt{\dfrac{2}{n}}$$. As n increases, the distribution converges to a delta function centered at 2, indicating that the probability of the sample mean equaling 2 approaches zero. This highlights the distinction between continuous random variables and specific values in probability theory.

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  • Understanding of the Central Limit Theorem
  • Knowledge of Normal distribution properties
  • Familiarity with concepts of convergence in probability
  • Basic grasp of continuous random variables
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  • Study the implications of the Central Limit Theorem in statistical inference
  • Explore the properties of delta functions in probability theory
  • Learn about convergence concepts in probability, such as almost sure convergence
  • Investigate the differences between discrete and continuous random variables
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Statisticians, data analysts, and students of probability theory seeking to deepen their understanding of sample means and their convergence properties.

MAXIM LI
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Homework Statement
## Let {X_n}_{n≥1}## be a sequence of iid random variables having a common density function
## f(x) = \begin{cases} xe^{-x} &\text{ for } x \ge 0 \\ 0 &\text{ otherwise }\end{cases}##

Let ##\bar{X}_n = \frac{1}{n}\sum_{i=1}^{n} X_i## where ##n=1,2,\ldots##. Then find ##\lim_{{n\to\infty}} P(\bar{X}_n=2)##
Relevant Equations
##\lim_{{n\to\infty}} P(\bar{X}_n=2)##
My first thought as well but I think the problem is deeper than that. I think that as the n tends towards infinity the probability of the the sample mean converging to the population mean is 1. Looking at proving this.
By the Central Limit Theorem the sample mean distribution can be approximated by a Normal distribution with $$\mu = 2,~\sigma = \sqrt{\dfrac{2}{n}}$$

As ##n\to \infty## this becomes a delta function centered at ##2##
 
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You're overcomplicating this. ##\overline{X}_n## is a continuous random variable so ##P(\overline{X}_n = a) = 0## for all ##a \in \mathbb{R}##. In particular
$$\lim_{n \to \infty} P(\overline{X}_n = 2)= \lim_{n \to \infty} 0 = 0$$
 
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