I am trying to solve expected value and variance of the random vector given by function: $$\begin{equation} p_x(x)=\left\{ \begin{array}{@{}ll@{}} \frac1\pi, & \text{if}\ x^2_1+x^2_2 < 1 \\ 0, & \text{otherwise} \end{array}\right. \end{equation} $$ Condition $$x^2_1+x^2_2$$ let me know that this is an unit circle in 3d-plane, so I can integrate from [-1 1] in both directions: $$ E(x)=\begin{bmatrix} \int^1_{-1}{x_1*\frac1\pi} \\ \int^1_{-1}{x_2*\frac1\pi} \\ \end{bmatrix} = \begin{bmatrix} 0 \\ 0 \end{bmatrix} $$ Is that right way of doing expected value? What about variance? I didnt quite catche how to figure out the variance. I have now probability theory course and some other course, which uses that part of probability theory. The other course is going on and probability theory has just started. Because of that I have asked questions here. Thanx.
2026-04-02 16:26:25.1775147185
Expected value and variance of a random vector
593 Views Asked by Bumbble Comm https://math.techqa.club/user/bumbble-comm/detail At
1
There are 1 best solutions below
Related Questions in PROBABILITY
- How to prove $\lim_{n \rightarrow\infty} e^{-n}\sum_{k=0}^{n}\frac{n^k}{k!} = \frac{1}{2}$?
- Is this a commonly known paradox?
- What's $P(A_1\cap A_2\cap A_3\cap A_4) $?
- Prove or disprove the following inequality
- Another application of the Central Limit Theorem
- Given is $2$ dimensional random variable $(X,Y)$ with table. Determine the correlation between $X$ and $Y$
- A random point $(a,b)$ is uniformly distributed in a unit square $K=[(u,v):0<u<1,0<v<1]$
- proving Kochen-Stone lemma...
- Solution Check. (Probability)
- Interpreting stationary distribution $P_{\infty}(X,V)$ of a random process
Related Questions in PROBABILITY-THEORY
- Is this a commonly known paradox?
- What's $P(A_1\cap A_2\cap A_3\cap A_4) $?
- Another application of the Central Limit Theorem
- proving Kochen-Stone lemma...
- Is there a contradiction in coin toss of expected / actual results?
- Sample each point with flipping coin, what is the average?
- Random variables coincide
- Reference request for a lemma on the expected value of Hermitian polynomials of Gaussian random variables.
- Determine the marginal distributions of $(T_1, T_2)$
- Convergence in distribution of a discretized random variable and generated sigma-algebras
Related Questions in PROBABILITY-DISTRIBUTIONS
- Given is $2$ dimensional random variable $(X,Y)$ with table. Determine the correlation between $X$ and $Y$
- Statistics based on empirical distribution
- Given $U,V \sim R(0,1)$. Determine covariance between $X = UV$ and $V$
- Comparing Exponentials of different rates
- Linear transform of jointly distributed exponential random variables, how to identify domain?
- Closed form of integration
- Given $X$ Poisson, and $f_{Y}(y\mid X = x)$, find $\mathbb{E}[X\mid Y]$
- weak limit similiar to central limit theorem
- Probability question: two doors, select the correct door to win money, find expected earning
- Calculating $\text{Pr}(X_1<X_2)$
Related Questions in RANDOM-VARIABLES
- Prove that central limit theorem Is applicable to a new sequence
- Random variables in integrals, how to analyze?
- Convergence in distribution of a discretized random variable and generated sigma-algebras
- Determine the repartition of $Y$
- What is the name of concepts that are used to compare two values?
- Convergence of sequences of RV
- $\lim_{n \rightarrow \infty} P(S_n \leq \frac{3n}{2}+\sqrt3n)$
- PDF of the sum of two random variables integrates to >1
- Another definition for the support of a random variable
- Uniform distribution on the [0,2]
Trending Questions
- Induction on the number of equations
- How to convince a math teacher of this simple and obvious fact?
- Find $E[XY|Y+Z=1 ]$
- Refuting the Anti-Cantor Cranks
- What are imaginary numbers?
- Determine the adjoint of $\tilde Q(x)$ for $\tilde Q(x)u:=(Qu)(x)$ where $Q:U→L^2(Ω,ℝ^d$ is a Hilbert-Schmidt operator and $U$ is a Hilbert space
- Why does this innovative method of subtraction from a third grader always work?
- How do we know that the number $1$ is not equal to the number $-1$?
- What are the Implications of having VΩ as a model for a theory?
- Defining a Galois Field based on primitive element versus polynomial?
- Can't find the relationship between two columns of numbers. Please Help
- Is computer science a branch of mathematics?
- Is there a bijection of $\mathbb{R}^n$ with itself such that the forward map is connected but the inverse is not?
- Identification of a quadrilateral as a trapezoid, rectangle, or square
- Generator of inertia group in function field extension
Popular # Hahtags
second-order-logic
numerical-methods
puzzle
logic
probability
number-theory
winding-number
real-analysis
integration
calculus
complex-analysis
sequences-and-series
proof-writing
set-theory
functions
homotopy-theory
elementary-number-theory
ordinary-differential-equations
circles
derivatives
game-theory
definite-integrals
elementary-set-theory
limits
multivariable-calculus
geometry
algebraic-number-theory
proof-verification
partial-derivative
algebra-precalculus
Popular Questions
- What is the integral of 1/x?
- How many squares actually ARE in this picture? Is this a trick question with no right answer?
- Is a matrix multiplied with its transpose something special?
- What is the difference between independent and mutually exclusive events?
- Visually stunning math concepts which are easy to explain
- taylor series of $\ln(1+x)$?
- How to tell if a set of vectors spans a space?
- Calculus question taking derivative to find horizontal tangent line
- How to determine if a function is one-to-one?
- Determine if vectors are linearly independent
- What does it mean to have a determinant equal to zero?
- Is this Batman equation for real?
- How to find perpendicular vector to another vector?
- How to find mean and median from histogram
- How many sides does a circle have?
It is often the case that some introductory course on probability theory requires some knowledge from multivariate calculus. To evaluate the variance matrix, it is much more efficient to use polar coordinate change $$(x_1,x_2)=(r\cos\theta,r\sin \theta).$$ Then $dx_1dx_2 = rdrd\theta$, and we have $$ \frac{1}{\pi}\int_{x_1^2+x_2^2<1}x_1^2\;dx_1dx_2=\frac{1}{\pi}\int_0^{2\pi}\int_0^1 r^3\cos^2 \theta\;drd\theta=\frac{1}{4}, $$ $$ \frac{1}{\pi}\int_{x_1^2+x_2^2<1}x_1x_2\;dx_1dx_2=\frac{1}{\pi}\int_0^{2\pi}\int_0^1 r^2\cos\theta\sin\theta\;drd\theta=0, $$ and the variance of $X_2$ is the same as that of $X_1$.