List questions from expectation

Published on 20 Aug 2014 - 6:48

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how to compute $E[e^{a^2/2}N^2]$, $N$ is $\mathcal{N}(0,1)$

Published on 20 Aug 2014 - 9:45

347

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Conditional probability with a normal distribution

Published on 20 Aug 2014 - 17:42

143

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Integrability condition

Published on 21 Aug 2014 - 11:59

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What is the expected value of the number of anchors of $S$?

Published on 22 Aug 2014 - 1:45

142

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About putting $n$ distinct balls into $n$ distinct boxes.

Published on 22 Aug 2014 - 2:41

304

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Brainteaser: Player A has £1, Player B £99. They flip a coin. The loser pays the other £1. Expected number of games before one is bankrupt?

Published on 22 Aug 2014 - 5:47

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Do we need $\tau \leq \nu$ to show $E(X_\tau)=E(X_\nu)$?

Published on 26 Mar 2026 - 8:15

52

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Using EM versus estimating all parameters directly

Published on 28 Mar 2026 - 10:03

47

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Random Variable Worded Problem

Published on 23 Aug 2014 - 8:40

1k

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Centered independent increments process is a martingale

Published on 23 Aug 2014 - 13:02

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Equivalence of two formulas for variance and covariance

Published on 24 Aug 2014 - 23:14

181

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How to apply the strong Markov property in this case?

Published on 26 Aug 2014 - 8:02

70

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Why is this a geometric distribution?

Published on 26 Aug 2014 - 8:47

915

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Calculating expected value for a Binomial random variable

Published on 28 Mar 2026 - 20:49

List Question

expected value product dependent random variables

how to compute $E[e^{a^2/2}N^2]$, $N$ is $\mathcal{N}(0,1)$

Conditional probability with a normal distribution

Integrability condition

What is the expected value of the number of anchors of $S$?

About putting $n$ distinct balls into $n$ distinct boxes.

Brainteaser: Player A has £1, Player B £99. They flip a coin. The loser pays the other £1. Expected number of games before one is bankrupt?

Do we need $\tau \leq \nu$ to show $E(X_\tau)=E(X_\nu)$?

Using EM versus estimating all parameters directly

Random Variable Worded Problem

Centered independent increments process is a martingale

Equivalence of two formulas for variance and covariance

How to apply the strong Markov property in this case?

Why is this a geometric distribution?

Calculating expected value for a Binomial random variable

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