probability - Proof explanation - weak law of large numbers - Mathematics Stack Exchange

Let $(X_i)$ be i.i.d. random variables with mean $\mu$ and finite variance. Then $$\dfrac{X_1 + \dots + X_n}{n} \to \mu \text{ weakly }$$ I have the proof here: What I don't understand is, why it

proof explanation - Central Limit Theorem - Wikipedia article - Mathematics Stack Exchange

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statistics - Expectation of square of random variable and their mean. - Mathematics Stack Exchange

The Law of Large Numbers - by Tivadar Danka

probability - Proof explanation - weak law of large numbers - Mathematics Stack Exchange

Entropy, Free Full-Text

probability theory - Law of large numbers for dependent random variables with fixed covariance - Mathematics Stack Exchange

Proof of the Law of Large Numbers Part 2: The Strong Law, by Andrew Rothman

probability - Weak law vs strong law of large numbers - intuition - Cross Validated

By mimicking the proof of Theorem 8.7 (Weak Law of

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Weak Law of Large Numbers (WLLN). Overview, by Pablo Kowalski Kutz