Covariance Matrix Of a Random Vector

Definition and example of the covariance matrix of a random vector.

Rating Rating Rating Rating Rating 
Views: 16,288
Added: 4 years
Runtime: 6:24
Comments: 11

Tags for this video:  

Find more videos in the: "Education"
Uploaded by: Neal Patwari
See more videos uploaded by Neal Patwari

Related Videos:

Kamal haasan Karan Thapar
Rating Rating Rating Rating Rating 
Views: 208354
One of the icons of South Indian Actor, screenwriter, Director, Producer, Dancer, Singer, Artist, Teacher.. Oh dear, and so much more.. Here is an...
How To Solve For Covariance
Rating Rating Rating Rating Rating 
Views: 32023
Looking for a tutorial on How To Solve For Covariance? This practical instructional video explains accurately how it's done, and will help you get...
Simple Covariance Matrix
Rating Rating Rating Rating Rating 
Views: 2378
Stochastic Processes Part 4
Statistics 101: The Covariance Matrix
Rating Rating Rating Rating Rating 
Views: 19218
Statistics 101: The Covariance Matrix In this video we discuss the anatomy of a covariance matrix. Unfortunately covariance matrices are often...
Discrete Random Matrices -- 2009 Moursund Lectures, Day 3
Rating Rating Rating Rating Rating 
Views: 3676
Terence Tao, 2006 Fields Medal Recipient University of California, Los Angeles Lecture three of a three part series Abstract: The spectral theory...
Statistics 101: Understanding Covariance
Rating Rating Rating Rating Rating 
Views: 32940
Statistics 101: Covariance. In this video we discuss the very basics of what covariance is (and isn't) using two real-world examples; stock market...
Poisson Processes Derivation
Rating Rating Rating Rating Rating 
Views: 6408
How to derive the pmf of the Poisson random process from the pmf of an approximating Binomial random process, by letting the block duration go to...
Sample Covariance and Correlation
Rating Rating Rating Rating Rating
Views: 10453
Calculation of sample covariance and correlation
Statistics 101: Introduction to the Poisson Distribution
Rating Rating Rating Rating Rating 
Views: 28996
Statistics 101: Introduction to the Poisson Distribution In this video we discuss the basic characteristics of the Poisson Distribution using a...
Lec 15 | MIT 18.085 Computational Science and Engineering I
Rating Rating Rating Rating Rating 
Views: 9687
Numerical methods in estimation: recursive least squares and covariance matrix A more recent version of this course is available at:...
Correlation & Covariance
Rating Rating Rating Rating Rating 
Views: 167603
Covariance is a measure of relationship (or co-movement) between two variables. Correlation is just the translation of covariance into a UNITLESS...
(PP 6.1) Multivariate Gaussian - definition
Rating Rating Rating Rating Rating 
Views: 10908
Introduction to the multivariate Gaussian (or multivariate Normal) distribution.
Linear Regression - Least Squares Criterion Part 1
Rating Rating Rating Rating Rating 
Views: 53052
Linear Regression - Least Squares Criterion. In this video I just give a quick overview of linear regression and what the 'least square criterion'...
Correlation Coefficient
Rating Rating Rating Rating Rating 
Views: 38280
A step by step problem on how to use the Correlation Coefficient formula.
Multivariate Gaussian Random Vectors - Part 2 - Properties
Rating Rating Rating Rating Rating 
Views: 2737
Three important properties of a Gaussian Random Vector.
Matrices to solve a vector combination problem
Rating Rating Rating Rating Rating 
Views: 136855
More free lessons at: Using matrices to figure out if some combination of 2 vectors can create a 3rd...
Maximum Likelihood Example: Normal
Rating Rating Rating Rating Rating 
Views: 50422
The use of maximum likelihood estimation to estimate the mean of a normally distributed random variable.
Lecture - 32 Gaussian Random Processes
Rating Rating Rating Rating Rating 
Views: 15401
Lecture Series on Communication Engineering by Prof.Surendra Prasad, Department of Electrical Engineering ,IIT Delhi. For more details on NPTEL...
Covariance matrix
Rating Rating Rating Rating Rating 
Views: 69255
A covariance matrix, in finance, is a square matrix that contains covariances between portfolio assets. Because, for example, the element in row...
How to Calculate a Beta
Rating Rating Rating Rating Rating 
Views: 28579
How to Calculate a Beta Please visit my website:
Calculating a Sample Standard Deviation (for ungrouped data)
Rating Rating Rating Rating Rating 
Views: 25942
© Maky Manchola - We present an example on how to calculate a sample standard deviation for ungrouped data.
Kalman Filtering
Rating Rating RatingRatingRating
Views: 24676
This video is the result of a "Kalman Filtering" and Video Tracking Lab for my ES453 Computer Vision Course. The purpose of the video tracker is to...
Mod-01 Lec-22 Transformations of Random Vectors
Rating Rating Rating Rating Rating
Views: 1794
Probability and Statistics by Dr.Somesh Kumar,Department of Mathematics,IIT Kharagpur. For more details on NPTEL visit
Linear Independence and Linear Dependence, Ex 1
Rating Rating Rating Rating Rating 
Views: 144451
Need a LIVE tutor to help answer a question? Check out the people at...
Lecture 3 | Machine Learning (Stanford)
Rating Rating Rating Rating Rating 
Views: 136443
Help us caption and translate this video on Lecture by Professor Andrew Ng for Machine Learning (CS...


Author Bruno Antunes (3 years)
@armanrainy Thank you for the answer. I got what you told. Actually, my
knowledge’s about statistics are not very good. But I solved the problem
using another way. I realized that I didn’t need do find the covariance
matrix in my case. But, anyway, thank you for the help!

Author vickytruong0509 (1 year)
thank you, very helpful video

Author Natnael Simachew (10 months)
Thank you very much. Big point few words and few minutes.

Author Mohan Vamsi (1 year)
Thank you that was very useful

Author armanrainy (3 years)
@tritile Hi(sorry about my English). I think you didn't get the meaning of
random variables. when we say X it means we have several matrices and it
makes our data set. for example, X is a 3*1 matrix which means three
different experiment results about 3 parameters( like
density,temperature,pressure). When we say X it means we have done this
experiment N times (so we have n 3*1 matrices) and we want to find the
covariance matrix.your matlab result is caused by having just 1

Author Bruno Antunes (4 years)
@npatwari I'm sorry to bother you For example, I have the vector V=[ 2; 3;
5] so I'll make my matrix M=[2 3 5; 2 3 5; 2 3 5] and then cov(M)? I guess
I dind't understand what you mean, because I tried this way and MatLab gave
me one matrix filled by zeros I'd be glad if you help me thanks

Author slatun (3 years)
You are GOD !!!

Author maeseloger (2 years)
That is some godlike pulse you have to be able to write this with a mouse
in Paint...

Author Bruno Antunes (4 years)
Do you know how to use this function on MatLab? I'm trying to find the
covariance of a vector, but it gives me a single number, not a matrix

Author Neal Patwari (4 years)
@tritile You need many realizations of that vector in order to estimate the
covariance matrix. So, however you measured or came up with that one
vector, do it N times, and then send the cov() function all of the
realizations of the random vector together (in a matrix). Then Matlab will
return a covariance matrix.

Embed Video:


Search Video

Top Videos

Top 100 >>>


Analyse website