Covariance between functions of 3 random variables

In summary, to find cov(Y,Z) where Y = 2X_1 - 3X_2 + 4X_3 and Z = X_1 + 2X_2 - X_3, you need to expand the expression using the given information, including the variances of the X_j. However, the given values for E(Y) and E(Z) appear to be incorrect, so those should be double checked before proceeding with the calculation.
  • #1
EvenSteven
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Find [tex]cov(Y,Z)[/tex] where [tex] Y = 2X_1 - 3X_2 + 4X_3[/tex] and [tex]Z = X_1 + 2X_2 - X_3[/tex]
Information given [tex]E(X_1) =4[/tex]
[tex]E(X_2) = 9 [/tex]
[tex]E(X_3) = 5[/tex]
[tex]E(Y) = -7[/tex]
[tex]E(Z) = 26[/tex]

I tried expanding cov(Y,Z) = E(YZ) - E(Y)E(Z) but can't figure out how to calculate E(YZ)
 
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  • #2
EvenSteven said:
Find [tex]cov(Y,Z)[/tex] where [tex] Y = 2X_1 - 3X_2 + 4X_3[/tex] and [tex]Z = X_1 + 2X_2 - X_3[/tex]
Information given [tex]E(X_1) =4[/tex]
[tex]E(X_2) = 9 [/tex]
[tex]E(X_3) = 5[/tex]
[tex]E(Y) = -7[/tex]
[tex]E(Z) = 26[/tex]

I tried expanding cov(Y,Z) = E(YZ) - E(Y)E(Z) but can't figure out how to calculate E(YZ)

You have an expression for Y and another expression for Z, both of them as linear combinations of the X_j, so you can expand out the product. However, you will need some information you have not written here: you need to know that variances of the X_j in order to complete the calculation. If you were not told those (or some equivalent information) there is no hope of obtaining numerical answers; you can still give a formula but it will contain some unevaluated input constants.

Note also that there is something wrong with the given information: from EX1 = 4, EX2 = 9 and EX3 = 5, it follow that EY = E(2X1 - 3X2 + 4X3) = 2(4) - 3(9) + 4(5) = +1, not the given value -7. You should also check the value of EZ.
 
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1. What is covariance between functions of 3 random variables?

Covariance between functions of 3 random variables is a measure of how much the variables change together. It is a statistical tool used to analyze the relationship between three random variables and how they vary in relation to each other.

2. How is covariance between functions of 3 random variables calculated?

To calculate covariance between functions of 3 random variables, you need to first calculate the covariance between each pair of variables. Then, you can use these values to calculate the overall covariance between the three variables using the formula: Cov(X,Y,Z) = E[(X-E[X])(Y-E[Y])(Z-E[Z])].

3. What does a positive covariance between functions of 3 random variables mean?

A positive covariance between functions of 3 random variables indicates that the variables tend to change in the same direction. This means that an increase in one variable is associated with an increase in the other two variables.

4. What does a negative covariance between functions of 3 random variables mean?

A negative covariance between functions of 3 random variables indicates that the variables tend to change in opposite directions. This means that an increase in one variable is associated with a decrease in the other two variables.

5. How is covariance between functions of 3 random variables interpreted?

The magnitude of the covariance between functions of 3 random variables can be interpreted as a measure of the strength of the relationship between the variables. A larger covariance indicates a stronger relationship, while a smaller covariance indicates a weaker relationship. However, it is important to note that covariance only measures the direction and strength of the relationship, and does not imply causation between the variables.

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