Does the magnitude of covariance have any real meaning?

  • Context: MHB 
  • Thread starter Thread starter dhiraj
  • Start date Start date
  • Tags Tags
    Covariance Magnitude
Click For Summary
SUMMARY

The discussion centers on the understanding of the covariance formula, specifically cov(x,y)=\frac{\sum(x_i - \bar{x})(y_i - \bar{y})}{n-1}. Participants highlight that the numerator's multiplication of deviations indicates the relationship between changes in variables x and y. A covariance value, such as 50 versus 30, signifies the strength of their co-movement, but a single covariance value lacks intuitive meaning without context. The conversation emphasizes the necessity of comparing covariance values to derive meaningful insights.

PREREQUISITES
  • Understanding of statistical concepts such as covariance and variance
  • Familiarity with the formula for sample covariance
  • Knowledge of mean calculations and deviation from the mean
  • Basic grasp of positive and negative relationships in data sets
NEXT STEPS
  • Explore the implications of covariance in multivariate analysis
  • Learn about the relationship between covariance and correlation coefficients
  • Study how to interpret covariance in the context of regression analysis
  • Investigate the differences between covariance and variance in practical applications
USEFUL FOR

Statisticians, data analysts, and students studying statistics who seek to deepen their understanding of covariance and its applications in data analysis.

dhiraj
Messages
3
Reaction score
0
The title of the question may not be clear. But that is the real difficulty I am facing. I am not able to understand logic behind coming up with this formula for covariance.

We know that the sample covariance formula is:-

[math]cov(x,y)=\frac{\sum(x_i - \bar{x})(y_i - \bar{y})}{n-1}[/math]

I am not able to understand the logic behind the numerator. Why are we multiplying the terms. I mean, I know we need to find the change in x is appearing along with change in y (if they co-vary), so this formula will give direction of that change in terms of sign of the number that you get after substituting the values in the formula. And also we will be able to compare e.g. Having covariance of 50 for example is more of proof of x and y moving together than having it as 30. So their order will make sense. But if you just think of a single value of covariance without having to compare it with anything else, does it have any real intuitive meaning (just the number in itself)? For example in case of variance or standard deviation one can easily see that it is average number of 'deviation from the mean' per data point in the sample. But here in case of covariance, I am not able to come up with any such intuitive understanding.
 
Physics news on Phys.org
dhiraj said:
The title of the question may not be clear. But that is the real difficulty I am facing. I am not able to understand logic behind coming up with this formula for covariance.

We know that the sample covariance formula is:-

[math]cov(x,y)=\frac{\sum(x_i - \bar{x})(y_i - \bar{y})}{n-1}[/math]

I am not able to understand the logic behind the numerator. Why are we multiplying the terms. I mean, I know we need to find the change in x is appearing along with change in y (if they co-vary), so this formula will give direction of that change in terms of sign of the number that you get after substituting the values in the formula. And also we will be able to compare e.g. Having covariance of 50 for example is more of proof of x and y moving together than having it as 30. So their order will make sense. But if you just think of a single value of covariance without having to compare it with anything else, does it have any real intuitive meaning (just the number in itself)? For example in case of variance or standard deviation one can easily see that it is average number of 'deviation from the mean' per data point in the sample. But here in case of covariance, I am not able to come up with any such intuitive understanding.

Hi dhiraj! Welcome to MHB! (Smile)

It seems you already know.

If both values in the numerator are positive they provide a positive product.
And if both values are negative they also provide a positive product.
So if the values co-vary in a positive sense, we'll get a strong positive value, as we should.

A single value does indeed not make much sense.
We cannot derive a covariance, and neither for that matter, can we derive a standard deviation (for the same reason).
 

Similar threads

  • · Replies 3 ·
Replies
3
Views
2K
  • · Replies 4 ·
Replies
4
Views
3K
  • · Replies 1 ·
Replies
1
Views
5K
  • · Replies 18 ·
Replies
18
Views
3K
  • · Replies 5 ·
Replies
5
Views
5K
  • · Replies 0 ·
Replies
0
Views
2K
  • · Replies 43 ·
2
Replies
43
Views
5K
Replies
4
Views
1K
  • · Replies 1 ·
Replies
1
Views
2K
  • · Replies 4 ·
Replies
4
Views
1K