Question

What would be the necessary & sufficient cond.s for the distribution of $\bar X$ the same as $X_i$s if $X_i$s are i.d but not Gaussian r.v.s?

score 43 · Answer 1 · 2020-03-25 22:48:05

43

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What would be the necessary & sufficient cond.s for the distribution of $\bar X$ the same as $X_i$s if $X_i$s are i.d but not Gaussian r.v.s?

Published on 25 Mar 2020 - 22:48

score 55 · Answer 2 · 2020-03-28 01:57:55

55

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Show $n^{-p}*S_{n} \to 0$ in probability

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score 43 · Answer 3 · 2026-02-23 04:33:28

43

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score 250 · Answer 4 · 2020-04-02 12:49:49

250

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score 18 · Answer 5 · 2026-03-28 09:32:55

18

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42

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score 75 · Answer 7 · 2020-04-13 07:46:05

75

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190

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score 80 · Answer 12 · 2026-02-23 06:22:52

80

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$\lim_{n \rightarrow \infty} \sum_{k = 0}^n \frac{e^{-n} n^k}{k!}$ =?

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score 341 · Answer 13 · 2026-03-27 00:06:39

341

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score 156 · Answer 14 · 2026-03-27 00:04:47

156

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score 88 · Answer 15 · 2020-04-24 23:54:56

88

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List Question

What would be the necessary & sufficient cond.s for the distribution of $\bar X$ the same as $X_i$s if $X_i$s are i.d but not Gaussian r.v.s?

Show $n^{-p}*S_{n} \to 0$ in probability

Gaussian distribution distance function

a marksman scores at each shot either 10, 9, 8, 7 or 6 with respective probabilities 0.5, 0.3, 0.1, 0.05, 0.05.

Why is $H_j=-\infty$ almost surely when $E(H_1)\in [-\infty, 0)$

Central limit theorem on linear combination of activations in a neural network

Estimate using central limit theorem

Convergence in distribution equaling a certain value

Esseen's inequality for random series?

Asymptotic distribution of sum of independent, not identically distributed, bernoulli distribution with poisson tail probability

Central Limit Theorem for Linear Combination of Poisson Variables

$\lim_{n \rightarrow \infty} \sum_{k = 0}^n \frac{e^{-n} n^k}{k!}$ =?

Using Lyapunov Condition show that a sequence of Poisson-Binomial random variables converge in distribution to the standard normal.

Determining norming and centering constants to guarantee weak convergence to a non-degenerate distribution

Central limit theorem for one-dependent Bernoulli random variables

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