Questions tagged [random-variables]

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

A random variable $X: \Omega \to E$ is a measurable function from a set of possible outcomes $\Omega$ to a measurable space $E$. The technical axiomatic definition requires $\Omega$ to be a sample space of a probability triple. Usually $X$ is real-valued.

The probability that $X$ takes on a value in a measurable set $S \subseteq E$ is written as :

$$P(X \in S) = P(\{ \omega \in \Omega|X(\omega) \in S\})$$

where $P$ is the probability measure equipped with $\Omega$.

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Why is the function $\Omega\rightarrow\mathbb{R}$ called a random variable?

I do not understand the relation of a normal variable "x", which is to me just a placeholder for an element of a set, and a random variable, which is a mapping from the set of all possible events to $\mathbb{R}$. To make the question more concrete,…
user13247
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How to find the PDF of one random variable when the PDF of another random variable and the relationship between the two random variables are known?

The probability density function of random variable X is given as $ f_x(x) = \lambda e^ {-\lambda x} , x \ge 0. $ A new random variable $ Y = e^ {-\lambda X}$ is formed. Find the PDF of Y.
PasanW
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Covariance of random variables which don't have variances.

Whether there is a covariance of two random variables, which both don't have variances? Is existence of the variances of two random variables implies existence of covariance? Thanks in advance.
adam
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Why does $\mathbf{Var}(X) = \mathbf{Var}(-X)$ for random variable $X$?

Question from UCLA Math GRE study packet, Problem Set 2, Number 4: http://www.math.ucla.edu/~cmarshak/GREProb.pdf Let $X$ and $Y$ be random variables. Which of the following is always true? \begin{align} ...\\ (II) \ \mathbf{Var}(X) =…
maurice
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Finding E(x) from E(ln(x)).

Say you have $\operatorname{E}[\ln(x)]=\mu$, is there a way to find $\operatorname{E}[x]$? This seems like a really simple question but I can't figure it out. Any help would be appreciated.
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The expected value and standard deviation of $|X-Y|$ where $X$ and $Y$ are random variables

Suppose we have two independent random variables $X$ and $Y$, with expected values and standard deviations of $(\mu_X,\sigma_X)$ and $(\mu_Y,\sigma_Y)$, respectively. Can we say anything about the expected value and standard deviation of $|X-Y|$? If…
sodiumnitrate
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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 distributed variables, $\mathrm{Geo}(p)$. Apparently, $Z$…
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Does every random variable(continous) has a probability density function?

what is the criterion for a random variable(continous) for existence of probability density function for it? Could you provide some cases of random variable(continous) where pdf ceases to exist.
Vineel Kumar Veludandi
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The repetition pattern of a random integer sequence

Here is a problem that bothers me, could some one grand me some help? There is a sequence of N random integers, {$X_1,X_2,...,X_N$}. Each $X_i$ is uniformly chosen from a integer set {1,...,M}. For each specific values of the sequence,…
Eric
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Distribution of sum of not quite independent normal random variables.

I have independent $X_i$ with mean $0$ and variance $1$. They are normally distributed. From the $X_i$ I construct $Y_i$ = $X_i$ + $X_{i+1}$. The $Y_i$ aren’t independent. I’m curious to know the distribution of $\frac{\sum_{i=1}^n Y_i}{\sqrt{n}}$.…
quiet
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A counterexample that marginal convergence in law does not imply joint convergence in law

I just encountered the following counterexamle that should illustrate that marginal convergence in distribution does not imply joint convergence in distribution: Let U and V be independent standard normal random variables and…
s_2
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A continuous random variable map by continuous function will become continuous?

Let $X$ be a continuous random variable and let $g$ be a non-constant real-valued continuous function. Prove or disprove that $g(X)$ is a continuous random variable. Note : Here it is assumed that $g(X)$ is a random variable.
karfai
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The concept of random variable

I'm reading Bernt Oksendal's "Stochastic Differential Equations" (edition 6) and I got quite confused on the conceptions. Please kindly help. I don't understand what is an event in the definition of random variable Definition: A random variable $X$…
athos
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Naming random variables

What is wrong with the statement, "If $x$ is a continuous random variable, with probability density function $f(x)$, the probability that it lies in $(x_1,x_2)$ is $$P(x_1
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How to calculate the density of $Y=X^4$

Let $X$ be a uniformly distributed variable on $[0,1]$. What is the density of $Y=X^4$? How do you calculate it? Thank you
Ryan
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