List questions from expectation

Published on 13 Jan 2014 - 4:46

240

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Calc expected value of 5 random number with uniform distribution

Published on 02 Apr 2026 - 22:43

267

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Covariance and Expectation of Discrete Random Variables

Published on 11 Apr 2026 - 0:55

26

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independence of x and pdf

Published on 15 Jan 2014 - 21:27

1.2k

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Expectation of brownian motion at hitting time

Published on 31 Mar 2026 - 3:29

49

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Expected value of measurements associated to die rolls

Published on 11 Apr 2026 - 2:44

499

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Probability that the value at time T from one geometric Brownian motion process is greater than the value from another GBM

Published on 12 Apr 2026 - 0:35

1.2k

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Conditional expectation inequality

Published on 11 Apr 2026 - 9:03

82

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How to prove that if $\int_t^\infty(s-t-\frac{1}{\lambda})\,f(s)\ ds =0$ for all $t\ge 0$ then $f(s)=\lambda\, \mathrm{e}^{-\lambda s}$

Published on 17 Jan 2014 - 23:15

128

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Law of Iterated Expectations in Card Draw

Published on 10 Apr 2026 - 16:31

166

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Conditional Expectation : Can't figure it out.

Published on 22 Jan 2014 - 16:13

2.2k

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Expected sum of all the n-sided dice rolls until we get n

Published on 02 Apr 2026 - 5:23

72

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Why is $E(X^2)$ not equal to the sum of $(x^2 \cdot P(x^2))$ instead of $x^2 \cdot P(x)$

Published on 24 Jan 2014 - 14:43

181

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expectation conditioned on sigma fields

Published on 24 Jan 2014 - 20:01

301

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What's $\mathbb E[\mathbb E[Y|X]|Y]$? Is it well-defined?

Published on 10 Apr 2026 - 11:41

List Question

variance of iid random variables

Calc expected value of 5 random number with uniform distribution

Covariance and Expectation of Discrete Random Variables

independence of x and pdf

Expectation of brownian motion at hitting time

Expected value of measurements associated to die rolls

Probability that the value at time T from one geometric Brownian motion process is greater than the value from another GBM

Conditional expectation inequality

How to prove that if $\int_t^\infty(s-t-\frac{1}{\lambda})\,f(s)\ ds =0$ for all $t\ge 0$ then $f(s)=\lambda\, \mathrm{e}^{-\lambda s}$

Law of Iterated Expectations in Card Draw

Conditional Expectation : Can't figure it out.

Expected sum of all the n-sided dice rolls until we get n

Why is $E(X^2)$ not equal to the sum of $(x^2 \cdot P(x^2))$ instead of $x^2 \cdot P(x)$

expectation conditioned on sigma fields

What's $\mathbb E[\mathbb E[Y|X]|Y]$? Is it well-defined?

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