Standard deviation of response

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SUMMARY

The discussion centers on calculating the standard deviation and understanding the correlation coefficient in the context of a linear model. It clarifies that a single variable's standard deviation is equivalent to its variance, as covariance applies only between two different variables. The correlation coefficient ranges from -1 to 1, indicating perfect negative to perfect positive correlation, respectively. Misconceptions regarding the formula for covariance are addressed, emphasizing that covariance cannot be expressed as standard deviation divided by mean.

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MahaRoho
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Homework Statement
I have to find the standard deviation
Relevant Equations
There are not any
part4.jpg
 
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MahaRoho said:
Homework Statement:: I have to find the standard deviation
Relevant Equations:: There are not any
I would think that this is not good enough. What form does the model have? Is the model a linear model? Are there equations for the mean and variance of the model?
 
The model is linear. The nominal values are the means of those parameters.
1. I need to know the standard deviation of a single variable that includes the covariance of that variable.
2. What is the value of correlation co efficient if the variables are fully correlated (I think it is 1), partially (0-1) and anti (0 to -1)?
 
MahaRoho said:
The model is linear.
Then you should start by writing down the general form of a linear model and then translate the additional information into statements about that model.
MahaRoho said:
The nominal values are the means of those parameters.
1. I need to know the standard deviation of a single variable that includes the covariance of that variable.
A single variable does not have a covariance, it has a variance.
CORRECTION: Although the covariance is defined as cov(X,Y)=E[(X-E[X])(Y-E[Y])], there is nothing that says that X and Y have to be different. If they are the same random variable, the covariance is the variance.
MahaRoho said:
2. What is the value of correlation co efficient if the variables are fully correlated (I think it is 1)
Yes.
MahaRoho said:
, partially (0-1)
Possibly. Some people would include the negative values (-1,1)
MahaRoho said:
and anti (0 to -1)?
Yes. That is also called "negative correlation" and "inverse correlation". I call variables "correlated" even if it is negative and if I want to distinguish positive from negative, I call them "positively correlated" or "negatively correlated". But others might prefer other terminology. In any case, the term "correlation" or "correlation coefficient" includes both the positive and negative cases.
 
Last edited:
Thanks a lot for the reply. Btw, I think I saw a formula on the internet like Covariance(x)=Standard deviation/ mean... Is that formula correct?
 
MahaRoho said:
Thanks a lot for the reply. Btw, I think I saw a formula on the internet like Covariance(x)=Standard deviation/ mean... Is that formula correct?
No, that is not correct. But I have corrected my comment about the covariance in post #4.
The definition of covariance of random variables X and Y is cov(X,Y)=E[(X-E[X])(Y-E[Y])].
 
Maybe a good starting point is writing down what the definition of sensitivity is.
 
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