- #1
rogo0034
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Homework Statement
Homework Equations
SS(x-(mean x))(y- (mean y) f(x,y) dxdy
(note: SS=integers for x and y)
The Attempt at a Solution
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rogo0034 said:"E[X]=∬x⋅y⋅f(x,y)dxdy"
did you mean E[XY] ?
rogo0034 said:I just got (x^3) for mu(x) and -((2x^3)/3) for mu(y)
Is this correct?
I would post my work, but it seems to make the image massive.
rogo0034 said:I understood half that... ha, I'm in an entry level stats course, you are blowing my mind, fyi.
Only in the inner limit. You MUST draw a picture. The inner integral is correct, x from 0 to y.rogo0034 said:right, but the bounds; 0<x<y<1 force me to put in variables when i integrate, right?
rogo0034 said:is this all correct?
i'm applying it to your formula: E[g(X,Y)]=∬g(x,y)f(x,y)dxdy
So do i have to now: E[1/36]=∬(1/36)(2)dxdy ??
EDIT: Ah, nevermind, after going through that it still comes up 1/36, so I'm assuming this is finally the Correlation Coefficient (1/36) ??
The correlation coefficient, also known as r, is a statistical measure that shows the strength and direction of the relationship between two variables. It is a number between -1 and 1, where -1 indicates a perfect negative correlation, 0 indicates no correlation, and 1 indicates a perfect positive correlation.
The correlation coefficient is calculated by dividing the covariance of the two variables by the product of their standard deviations. In simpler terms, it is the measure of how much the two variables move together, while taking into account their individual variabilities.
A positive correlation coefficient indicates that as one variable increases, the other variable also tends to increase. This means that the two variables have a direct relationship and move in the same direction.
A negative correlation coefficient indicates that as one variable increases, the other variable tends to decrease. This means that the two variables have an inverse relationship and move in opposite directions.
The correlation coefficient can be interpreted as a measure of the strength and direction of the relationship between two variables. A value close to 1 or -1 indicates a strong relationship, while a value close to 0 indicates a weak relationship. Additionally, the sign of the correlation coefficient also indicates the direction of the relationship.