# Second Borel-Cantelli Lemma

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## Statement

Let the events $E_n$ be independent.

Let the sum of the probabilities of the $E_n$ diverges to infinity.

Then the probability that infinitely many of them occur is $1$.

That is:

If $\ds \sum_{n \mathop = 1}^\infty \map \Pr {E_n} = \infty$ and the events $\ds \sequence {E_n}^\infty_{n \mathop = 1}$ are independent, then:

- $\ds \map \Pr {\limsup_{n \mathop \to \infty} E_n} = 1$

## Proof

Let $\ds \sum_{n \mathop = 1}^\infty \map \Pr {E_n} = \infty$.

Let $\sequence {E_n}^\infty_{n \mathop = 1}$ be independent.

It is sufficient to show the event that the $E_n$s did not occur for infinitely many values of $n$ has probability $0$.

This is just to say that it is sufficient to show that:

- $\ds 1 - \map \Pr {\limsup_{n \mathop \to \infty} E_n} = 0$

Noting that:

\(\ds 1 - \map \Pr {\limsup_{n \mathop \to \infty} E_n}\) | \(=\) | \(\ds 1 - \map \Pr {\set {E_n \text { i.o.} } }\) | ||||||||||||

\(\ds \) | \(=\) | \(\ds \map \Pr {\set {E_n \text{ i.o.} }^c}\) | ||||||||||||

\(\ds \) | \(=\) | \(\ds \map \Pr {\paren {\bigcap_{N \mathop = 1}^\infty \bigcup_{n \mathop = N}^\infty E_n}^c}\) | ||||||||||||

\(\ds \) | \(=\) | \(\ds \map \Pr {\bigcup_{N \mathop = 1}^\infty \bigcap_{n \mathop = N}^\infty E_n^c}\) | ||||||||||||

\(\ds \) | \(=\) | \(\ds \map \Pr {\liminf_{n \mathop \to \infty} E_n^c}\) | ||||||||||||

\(\ds \) | \(=\) | \(\ds \lim_{N \mathop \to \infty} \map \Pr {\bigcap_{n \mathop = N}^\infty E_n^c}\) |

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it is enough to show:

- $\ds \map \Pr {\bigcap_{n \mathop = N}^\infty E_n^c} = 0$

Since the $\sequence {E_n}^\infty_{n \mathop = 1}$ are independent:

\(\ds \map \Pr {\bigcap_{n \mathop = N}^\infty E_n^c}\) | \(=\) | \(\ds \prod^\infty_{n \mathop = N} \map \Pr {E_n^c}\) | ||||||||||||

\(\ds \) | \(=\) | \(\ds \prod^\infty_{n \mathop = N} \paren {1 - \map \Pr {E_n} }\) | ||||||||||||

\(\ds \) | \(\le\) | \(\ds \prod_{n \mathop = N}^\infty \map \exp {-\map \Pr {E_n} }\) | Exponential Function Inequality | |||||||||||

\(\ds \) | \(=\) | \(\ds \map \exp {-\sum_{n \mathop = N}^\infty \map \Pr {E_n} }\) | ||||||||||||

\(\ds \) | \(=\) | \(\ds 0\) |

This completes the proof.

$\blacksquare$

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This article, or a section of it, needs explaining.In particular: What is the motivation of the 'alternative' explanation below? It is exactly the same as the above proof, just wrapped by a logarithm, using the trivial relation $\map \ln {\exp x} = x$You can help $\mathsf{Pr} \infty \mathsf{fWiki}$ by explaining it.To discuss this page in more detail, feel free to use the talk page.When this work has been completed, you may remove this instance of `{{Explain}}` from the code. |

Alternatively, we can see:

- $\ds \map \Pr {\bigcap_{n \mathop = N}^\infty E_n^c} = 0$

by taking negative the logarithm of both sides to get:

\(\ds \map \ln {\map \Pr {\bigcap_{n \mathop = N}^\infty E_n^c} }\) | \(=\) | \(\ds -\map \ln {\prod_{n \mathop = N}^\infty \paren {1 - \map \Pr {E_n} } }\) | ||||||||||||

\(\ds \) | \(=\) | \(\ds -\sum_{n \mathop = N}^\infty \map \ln {1 - \map \Pr {E_n} }\) |

Since $-\map \ln {1 - x} \ge x$ for all $x > 0$, the result similarly follows from our assumption that $\ds \sum^\infty_{n \mathop = 1} \map \Pr {E_n} = \infty$.

$\blacksquare$

## Also see

## Source of Name

This entry was named for Émile Borel and Francesco Paolo Cantelli.