Questions about maps from a probability space to a measure space which are measurable.

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2
votes
1answer
64 views

Is this a Markov chain? [duplicate]

Let $\{\xi_n \}_{n \geq 1}$ be i.i.d random variables taking values on $\mathbb{Z}$. Let $\xi_0 = 0$. $S_n = \sum\limits_{i=1}^{n} \xi_i,$ where $S_0=0$ $Y_n = \sum\limits_{i=0}^{n} S_i$. My ...
1
vote
2answers
37 views

PMF of X: Number of trials to draw a chip

Let a bowl contain 10 chips of the same size and shape. One and only one of these chips is red. Continue to draw chips from the bowl, one at a time and at random and without replacement, until the red ...
0
votes
2answers
321 views

PMF of number of heads of 4 coin tosses

Let X equal the number of heads in four independent flips of a coin. Using certain assumptions, determine the pmf of X and compute the probability that X is equal to an odd number. I initially ...
0
votes
0answers
29 views

Let $X$ be uniformly distributed on $[0,1]$. Find the cumulative distribution function of $X-X^2$.

Let $X$ be a continuous random variable uniformly distributed on $[0,1]$. Find the cumulative distribution function of $X-X^2$. $P(X-X^2 \leq a)= P ( -X^2 + X - a \leq 0) = P ( -X^2 + X - a \leq 0| ...
0
votes
2answers
28 views

If $P(X \geq k) = p^k$, for $k=0, 1, 2,…$ then $P(X=k)=p^k(1-p)$

If $P(X \geq k) = p^k$, for $k=0, 1, 2,...$ then $P(X=k)=p^k(1-p)$ The converse is immediate but I don't know how to approach the direct implication.
0
votes
1answer
20 views

Transformation of Random Variable results in strange CDF

I'm trying to transform a RV according to $Y=X^{-a}$ with $a>0$ and X being uniformly distributed in $[0,A]$: $ F_X(x) = \begin{cases}0 & x<0 \\ x/A & 0\leq x \leq A \\ 1 ...
2
votes
1answer
65 views

If $X$ is Poisson, find the expectation of $\frac{1}{a+X}$

If $X$ is a Poisson random variable with $\Pr(X=k)=e^{-\lambda}\frac{\lambda^k}{k!}$ and $a>0$ then find the expectation of $\frac{1}{a+X}$ If I make use of ...
1
vote
1answer
26 views

How does $\mathcal{L}^1$-convergence of a series of $\mathcal{L}^1$ random variables imply that $\sup_{n \in \mathbb{N}} \mathbb{E}[|X_n|] < \infty$?

Let $(X_n)_{n \in \mathbb{N}}$ be a series of random variables with $\forall i: X_i \in \mathcal{L}^1(\Omega, \mathfrak{F}, P)$ and $X_n \rightarrow^{\mathcal{L}^1}X$. How do I show then, that ...
0
votes
1answer
44 views

Random variable modeling arthroscopic meniscal repair

The below problem is from my introductory stats textbook, the chapter on random variables and probability distributions. I don't even know what's being asked, much less how to answer it. Any clues? ...
-1
votes
1answer
44 views

finding out the probability density of a random process

I have to find out the probability density function of a random process with the following specifications:z(t)= xcos(wt)-ysin(wt) where x and y are two independent gaussian random variables. Now what ...
2
votes
1answer
34 views

Finding the mean and median of a probability density function

I suspect this is super-easy, but I haven't done any math in about ten years and I'm working with concepts that have been woefully explained... I need to find the mean and median of a continuous ...
0
votes
1answer
44 views

How to show that the following equation holds?

In Wikipedia appears the pdf's equation for $XY$ and $X/Y$, where $X$ and $Y$ are given independent random variables. The equations are For product $Z=XY$ ...
3
votes
2answers
58 views

$X,Y$ independent then $X+Y$, $X-Y$ independent as well?

My question is simple: If $X$, $Y$ are independent random variables then $X+Y$, $X-Y$ independent as well?
-1
votes
3answers
60 views

Mean and Variance of Y using Expectation Operator

Let $$ Y =\sum_{k=1}^N a_kX_k $$ be the weighted sum of N independent random variables, $ X_k, k = 1, ... , N $ , each having mean $ \mu _{X_i} $ and variance $ \sigma ^2_{X_i} $. The weights $a_k$ ...
0
votes
2answers
47 views

Uniform distribution in (0,1). P(X1+X2<=X3) and Gaussian RV with variance 1/4 and 1/9 , P(3V>=2U)

I'm appearing for a competitive examination and I find a lot of questions from probability involving $2$ or more random variables are very common. Please help me with the method on how to deal with ...
3
votes
1answer
17 views

$L^p$ integrability of products of Gaussian variables

Gaussian variables have moments of all orders, so by Hölder's inequality the product of two Gaussian variables $\xi$ and $\eta$ has finite $L^1$-norm: $$ \|\xi \cdot \eta\|_1 \leq \|\xi\|_2 \cdot ...
5
votes
0answers
79 views

Probability that a five is seen before any of the even numbers are seen

A fair die is repeatedly tossed. What is the probability that a five is seen before any of the even numbers are seen? I have my own solution below and just want someone to verify it. According ...
-1
votes
2answers
60 views

How to work with the mode of a probability mass function

How do you work with a probability mass function in determining stuff related to the mode. Here's the question I have $P(X=x) = {\theta^n}{{n}\choose{x}}({\frac{1-\theta}{\theta}})^x, x = ...
0
votes
1answer
113 views

Birthday Problem (Poisson Distribution)

I've been reading up on Poisson Distributions and have come across the following problem. My doubts are in Bold: What's the probability that in a room of n people, nobody shares the same birthday? ...
1
vote
1answer
36 views

statistics basic question on covariance

anyone would help me in a basic example? a fair coin is tossed, n times. X is the number of Head and Y is the number of Tails. what is the COV(X,Y).
1
vote
3answers
36 views

$X$ and $Y$ are independent and follow $U(0,1)$. Show $P(f(X) > Y) = \int_0^1 f(x) dx$

Let $X$ and $Y$ be two independent uniformly distributed r.v. on $[0,1]$, and $f$ is a continuous function from $[0,1]$ to $[0,1]$. Show that $P(f(X) > Y) = \int_0^1 f(x) dx$. I tried to prove ...
0
votes
0answers
25 views

Understanding Binomial random variables

I'm looking over Binomial random variables and I understand that $ \sum\limits_{k=0}^n k\binom{n}{k} p^k (1-p)^{n-k} = np $ from $\mathrm{Bin}(n,p)$ However, I don't understand how, if $S_n = ...
2
votes
1answer
34 views

Understanding Negative Binomial Random Variables

I'm trying to understand Negative Binomial Random Variables and have across the following: $ Z\sim \mathrm{NegBin}(n,p)$ if $Z = X_1 +\cdots+ X_r $ where $X_i's$ are independent identically ...
1
vote
1answer
13 views

Geometric Random Variable

I'm reading about Geometric Random variables from a book, which is as follows: $X_1, X_2,\ldots$ are independent identically distributed variables which are $\mathrm{Ber}(p)$ $$ Y = \min \{n\geq ...
1
vote
1answer
27 views

A LLN type theorem on the supremum of functions of a RV

Let $X_1,\dots,X_n$ be iid real valued random variables. Let $\mathcal{F}$ be a set of functions $f:\mathbb{R} \rightarrow \mathbb{R}$ such that $\mathbb{E}f(X_i) < \infty$ for all $f \in ...
0
votes
1answer
30 views

Understanding Geometric Random Variables

I'm looking up Geometric random variables, where $X_1, X_2....$ are independent identically distributed variables which are $Ber(p)$. The book says, $$ Y = \min \{n\geq 1| X_n = 1\} \sim Geo(p)$$ ...
2
votes
0answers
83 views

Probability problem related to discrete random variables, binomial distribution.

I've just solved an exercise related to discrete random variables and maybe to the binomial distribution as well. I would like to know if my solution is correct, so here goes the problem statement ...
2
votes
1answer
62 views

If $Y\ge 0$ almost surely and $X+Y \sim X$ then $Y=0$ almost surely

Let $X, Y$ be random variables on the same probability space such that $Y \ge 0$ almost surely and $X+Y$ and $X$ have the same distribution. Please resolve whether these conditions imply that ...
1
vote
1answer
52 views

Conditional expectation of symmetric Sigma algebra

Another exercise with conditional expectation that I have problems with. Let $\Omega=[-1,1]$, $\mathcal{F}=\mathcal{B}(\Omega)$, $\mathbb{P}=\frac{1}{2}\lambda$. Let X be a ...
5
votes
2answers
45 views

Finding all Borel measures $\mu_X$ such that $Y\sim \mathcal{N}(0,1) \Rightarrow XY \sim \mathcal{N}(0,1)$.

Find all Borel measures $\mu$ on $\mathbb{R}$ such that for every independent random variables such that $X \sim \mu$ and $Y\sim \mathcal{N}(0,1)$ we have $XY \sim \mathcal{N}(0,1)$. To be honest ...
2
votes
2answers
99 views

Expected distance between two vectors that belong to two different Gaussian distributions

Let $X$, $Y$ be two random variables that follow the Gaussian distributions with mean vectors $\mu_x$, $\mu_y$, and covariance matrices $\Sigma_x$, $\Sigma_y$, respectively. The probability density ...
1
vote
2answers
38 views

Prove Kolmogorov's SLLN by martingale.

Suppose $\xi_i$ are i.i.d. and $\mathbb E(|\xi_1|)\lt\infty$ Let $X_n=\sum_{i=1}^n\xi_i$ Then we have $\frac{X_n}{n}\to \mathbb E(|\xi_1|) $a.s. In the proof of this theorem: ...
1
vote
0answers
18 views

Simple random walk conditioning on non-return

Consider a simple symmetric random walk on $\mathbb{Z}$, $(S_t)_{t \geq 0}$, with $S_0=0$. Let $P_{k,j}$ be the probability that the walker hits the point $k$ without returning to the origin in ...
1
vote
0answers
42 views

What is meant by Stable Law?

I am reading a very complex paper consider a set of random variables $\left\{ X_{i}\right\} _{i=1}^{\infty }$ whose common distribution $F_{X}$ belong to the domain of attraction of an $\alpha ...
2
votes
0answers
45 views

Almost sure limit of $\log(X_1 + X_2 + … + X_n) - \log(n)$

Let $X_n$ be an i.i.d. sequence of positive random variables with expectation 2 and variance 1. What is the almost sure limit of $$\log(X_1 + X_2 + ... + X_n) - \log(n)$$ as $n \to \infty$ Would it ...
0
votes
1answer
49 views

Expectation of sum of $n$ random variables.

Let $X_1, X_2, X_3 \ldots, X_n$ be n random variables which take values from $\{+1,-1\}$ uniformly. Let $S_n$ be defined as $$S_n =|X_1+ X_2+ X_3+ \dots +X_n| $$ Find the expectation $E(S_n)$ of the ...
0
votes
1answer
71 views

The probability of having $k$ successes before $r$ failures in a sequence of independent Bernoulli trials

Problem Find the probability of having $k$ successes before $r$ failures in a sequence of independent Bernoulli trials with $p$ being the probability of success. I thought of using the Binomial ...
1
vote
2answers
20 views

Geometric and binomial distribution problem

Let $X \sim Bi(n,p)$, and $Y \sim \mathcal{G}(p)$. (a) Show that $P(X=0)=P(Y>n)$. (b) Find the number of kids a marriage should have so as the probability of having at least one boy is $\geq ...
1
vote
1answer
100 views

The probability of hitting a target at least twice, conditioned on hitting it at least once

I am working on some exercises related to random variables, since the subject is new to me, I feel a little insecure about my answers, I'll write the problem I've worked on to check if my solution is ...
0
votes
0answers
36 views

A R.V. is approximated as normal distribution by CLT. Can I use CLT again if I want to sum it with another R.V.?

My problem is, I have many independent normal random variables and since I need to have their squared distribution, I use Central Limit Theory to approximate the sum of its squared distribution as ...
1
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2answers
77 views

Is $\exp(-2\sin^2t)$ a characteristic function?

Is $\exp(-2\sin^2t)$ the characteristic function of some random variable?
1
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2answers
43 views

Deriving exponential distribution from geometric

Let $\lambda$ be the expected number of events in a unit time interval $[s,s+1]$ (events are independent of each other and of the time interval), and $T$ a continuous random variable that represents ...
1
vote
2answers
48 views

Showing that $\mathbb{E}|X\ln X| < \infty$ and $\mathbb{E}Z = \mathbb{E} X \ln X$ for given PDF of $Z$.

$X$ is real random variable such that $\mathbb{P}(X > 0) = 1$, $\mathbb{E}X^2 < \infty$, $\mathbb{E}X=1$. Let $Z$ be real random variable such that $\mathbb{P}(Z \in ...
0
votes
3answers
40 views

Variance of the sum of sample means

Let $X$ be a random variable with normal distribution with mean $ \theta$ and variance $ a>0$. Let $ Y $ be a random, variable with normal distribution with mean $\theta$ and variance $b>0$. ...
0
votes
0answers
31 views

Generate Correlated Normal and Log-Normal Random Variable

The standard approach for generating two normally distributed random variables some with correlation $\rho$ is explained here: Generate Correlated Normal Random Variables. Now let $X,Y$ be normally ...
1
vote
1answer
22 views

Bound on variance of random process when signal is known

I am reading this paper (link to a Nature paper, may not be accessible) and I encountered the following. I have very little experience in probability theory and I could not find much helpful in ...
3
votes
1answer
63 views

Convergence of discrete random variables, show $\frac{S_n}{\sqrt{n}}\to0$ a.s.

Let $X_n$ be a sequence of independent discrete real random variables, with discrete density $$p_{X_n}(x):=\Pr(X_n=x)= \cases{ 1-\frac1{n^2} & \text{if } x= 0\cr \frac1{2n^2} & \text{if ...
1
vote
1answer
37 views

Expected length of a random vector

I meet a basic definition about the expected length of a random vector when reading a paper: What is "expected length" How to roughly derive both equations (yellow part) (Is that Gamma ...
0
votes
1answer
38 views

Is the set $\limsup\limits_n\{\frac{X_n}{\log(n)}>\frac{1}{\lambda}\}$ equal to $\{\limsup\limits_n\frac{X_n}{\log(n)}>\frac{1}{\lambda}\}$?

Difference between $\limsup\limits_n\{\frac{X_n}{\log(n)}>\frac{1}{\lambda}\}$ and $\{\limsup\limits_n\frac{X_n}{\log(n)}>\frac{1}{\lambda}\}$ are the sets equal ? I think they would ...
0
votes
1answer
61 views

What is the mean and variance of $Y$, where $Y$ is sum of iid's

Here's my work for part a. I could use clarification on part b and d. Is part d the same as part a ($E[A_n] = E[Y]$) ? a) $$E[Y_n] = E[\frac{X_n}{2^n}]$$ ($X$'s are iid so...) $$= \frac{E[X]}{2^n} ...