The sample covariance of N observations of K

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    Covariance
In summary, the link provides information about covariance and its calculation for a sample of N observations of K variables. The sample covariance is represented by a K-by-K matrix, which is symmetric and contains estimated covariances between all possible pairs of variables. The covariance matrix must be of square size, such as 3x3, 4x4, 5x5, etc. and will have repeated values except on the diagonal, where the values will be equal to the corresponding variable's variance.
  • #1
DUET
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http://en.wikipedia.org/wiki/Covariance

I read from the above link that-

The sample covariance of N observations of K variables is the K-by-K matrix.

I am wondering-

Should "K-by-K" be "N-by-K" or not?
 
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  • #2
DUET said:
http://en.wikipedia.org/wiki/Covariance

I read from the above link that-

The sample covariance of N observations of K variables is the K-by-K matrix.

I am wondering-

Should "K-by-K" be "N-by-K" or not?
No. K-by-K is correct. Moreover it is symmetric. Each term in the matrix is the estimated covariance between two of the variables.
 
  • #3
Does it mean covariance matrix must be in square size, 3x3, 4x4, 5x5 etc?

It can never be 3x4, 4x7, 5x8 etc.
Correct?
 
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  • #4
Yes it has to be square. Remember that you need all possible values of Cov(X,Y) where X and Y are random variables. If you have N different variables then you have N*N or N^2 possibilities and since Cov(X,Y) = Cov(Y,X) you will have a lot of repeated values.
 
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  • #5
chiro said:
you will have a lot of repeated values.
I think every value will repeat twice. Am I correct?
 
  • #6
In general yes unless you are looking at the same random variable since Cov(X,X) = Var(X) on the diagonal elements.
 
  • #7
Yes! I am just taking off diagonal elements into account.
 
Last edited:

1. What is the definition of sample covariance?

The sample covariance of N observations of K is a statistical measure that describes the relationship between two variables in a sample dataset. It measures how much two variables vary together from their respective means.

2. How is sample covariance calculated?

Sample covariance is calculated by taking the sum of the product of the differences between each observation and their respective means for two variables, and dividing it by the total number of observations minus one.

3. What does a positive sample covariance indicate?

A positive sample covariance indicates that the two variables have a positive relationship, meaning that when one variable increases, the other tends to increase as well.

4. What does a negative sample covariance indicate?

A negative sample covariance indicates that the two variables have a negative relationship, meaning that when one variable increases, the other tends to decrease.

5. How does sample covariance differ from population covariance?

Sample covariance is calculated using a subset of observations from a larger population, while population covariance uses all of the observations in the population. Sample covariance is an estimate of the population covariance.

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