In this problem, we consider the probability distribution of a random variable X with:
• mean value μ_X = 40,
,
• standard deviation σ_X = 5.
Now, we consider the random variable Z defined as:
[tex]Z=X+X+X+X=4X\text{.}[/tex]
a. From probability theory, we know that a linear transformation of the type:
[tex]X\rightarrow Z=a+b\cdot X,[/tex]
changes the mean value and the standard deviation in the following way:
[tex]\begin{gathered} \mu_X\rightarrow\mu_Z=a+b\cdot\mu_X, \\ \sigma_X\rightarrow\sigma_Z=b\cdot\sigma_X\text{.} \end{gathered}[/tex]
In this case, we have a = 0 and b = 4, so we have that:
[tex]\begin{gathered} \mu_X\rightarrow\mu_Z=0+4\cdot\mu_X=4\cdot40=160, \\ \sigma_X\rightarrow\sigma_Z=4\cdot\sigma_X=4\cdot5=20\text{.} \end{gathered}[/tex]
b. The sum Z = X + X + X + X = 4X represents a new random variable that is 4 times the original random variable X. So Z is a random variable obtained from a specific linear transformation of the original random variable X.
c. Because (X + X + X + X)/4 = X, this sum represents just the original random variable X.
d. To compute μ_Z/4 and σ_z/4, we take into account that:
[tex]U=\frac{Z}{4}=\frac{(4X)}{4}=X\text{.}[/tex]
So the values of μ_Z/4 and σ_z/4 are just:
[tex]\begin{gathered} \mu_{\frac{Z}{4}}=\mu_X=40, \\ \sigma_{\frac{Z}{4}}=\sigma_X=5. \end{gathered}[/tex]
Answers
a.
[tex]\begin{gathered} \mu_Z=160, \\ \sigma_X=20. \end{gathered}[/tex]
b. The sum Z = X + X + X + X = 4X represents a new random variable that is 4 times the original random variable X. So Z is a random variable obtained from a specific linear transformation of the original random variable X.
c. Because (X + X + X + X)/4 = X, this sum represents just the original random variable X.
d.
[tex]\begin{gathered} \mu_{\frac{Z}{4}}=\mu_X=40, \\ \sigma_{\frac{Z}{4}}=\sigma_X=5. \end{gathered}[/tex]