Expected value and variance of max{Y_1,Y_2}

In summary, we have two independent random variables with a uniform distribution on the interval [1,2]. The maximum of these variables, X, has a cdf given by F_X(x) = 0 for x < 1, (x-1)^2 for 1 ≤ x < 2, and 1 for x ≥ 2. The p.d.f. is p(x) = 2(2-x) for 1 ≤ x ≤ 2 and 0 otherwise. The expected value of X is 4/3 and the variance is 1/18. However, there is a sign error in the derivation of the cdf and the correct cdf should be F_X(x) = 0 for x
  • #1
HaLAA
85
0

Homework Statement


Let Y_1,Y_2 be independent random variable with uniform distribution on the interval [1,2]. Define X=max{Y_1,Y_2}. Find p.d.f., expected value and variance.

Homework Equations

The Attempt at a Solution


Since $X=\max\{Y_1,Y_2\}$, this tells $Y_1$ and $Y_2$ must at most $x$. Thus, $\p(\max\{Y_1,Y_2\}\leq x)=\p(\{Y_1\leq x,Y_2\leq x\})=(2-x)^2$ with $1\leq x\leq 2$. So, the $c.d.f.$ of $X$ is
$$\p(x)=
\begin{cases}
0&\text{if $x<1$}\\
(2-x)^2 & \text{if $1\leq x\leq 2$}\\
1& \text{if $x>2$}
\end{cases}$$ where $a,b\in[1,2]$.
Then, the $p.d.f.$ is
$$p(x)=
\begin{cases}
2(2-x)&\;\;\text{if $1\leq a,b\leq 2$}\\
0&\;\;\text{otherwise}
\end{cases}$$
The expected value of $X$ is
$$E(X)=\int_{1}^{2}(4x-2x^2)\,dx=\frac{4}{3}$$
We also have
$$E(X^2)=\int_{1}^{2}(4x^2-2x^3)\,dx=\frac{11}{6}$$
Therefore, the variance is
$$V(X)=E(X^2)-(E(X))^2=\frac{11}{6}-\left(\frac{4}{3}\right)^2=\frac{1}{18}$$
 
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  • #2
There is a sign error in the derivation of the cdf.

This is also visible in the expectation value: The maximum of two variables cannot have an expectation value below the expectation value of its arguments (which is 3/2 > 4/3).

By the way, you can use inline LaTeX with double # instead of single $.
 
  • #3
HaLAA said:

Homework Statement


Let Y_1,Y_2 be independent random variable with uniform distribution on the interval [1,2]. Define X=max{Y_1,Y_2}. Find p.d.f., expected value and variance.

Homework Equations

The Attempt at a Solution


Since $X=\max\{Y_1,Y_2\}$, this tells $Y_1$ and $Y_2$ must at most $x$. Thus, $\p(\max\{Y_1,Y_2\}\leq x)=\p(\{Y_1\leq x,Y_2\leq x\})=(2-x)^2$ with $1\leq x\leq 2$. So, the $c.d.f.$ of $X$ is
$$\p(x)=
\begin{cases}
0&\text{if $x<1$}\\
(2-x)^2 & \text{if $1\leq x\leq 2$}\\
1& \text{if $x>2$}
\end{cases}$$ where $a,b\in[1,2]$.
Then, the $p.d.f.$ is
$$p(x)=
\begin{cases}
2(2-x)&\;\;\text{if $1\leq a,b\leq 2$}\\
0&\;\;\text{otherwise}
\end{cases}$$
The expected value of $X$ is
$$E(X)=\int_{1}^{2}(4x-2x^2)\,dx=\frac{4}{3}$$
We also have
$$E(X^2)=\int_{1}^{2}(4x^2-2x^3)\,dx=\frac{11}{6}$$
Therefore, the variance is
$$V(X)=E(X^2)-(E(X))^2=\frac{11}{6}-\left(\frac{4}{3}\right)^2=\frac{1}{18}$$
Your ##p(x)## is incorrect, because ##\{ \max(Y_1,Y_2) \leq x \} = \{ Y_1 \leq x \; \& \; Y_2 \leq x \}##, so ##P(X \leq x ) = P(Y_1 \leq x) \cdot P(Y_2 \leq x)## for independent ##Y_1,Y_2##.
 
Last edited:
  • #4
Ray Vickson said:
Your ##p(x)## is incorrect, because ##\{ \max(Y_1,Y_2) \leq x \} = \{ Y_1 \leq x \; \& \; Y_2 \leq x \}##, so ##P(X \leq x ) = P(Y_1 \leq x) \cdot P(Y_2 \leq x)## for independent ##Y_1,Y_2##.
The cdf is (x-1)^2?
 
  • #5
HaLAA said:
The cdf is (x-1)^2?

Not for all x, no, but maybe for some x. Anyway, you tell me!
 
  • #6
Ray Vickson said:
Not for all x, no, but maybe for some x. Anyway, you tell me!
For x from 1 to 2, (x-1)^2
For x below 1, it is 0
For x greater than 2, it is 1
 
  • #7
HaLAA said:
For x from 1 to 2, (x-1)^2
For x below 1, it is 0
For x greater than 2, it is 1

Correct. You could write it in LaTeX using the "cases" command, exactly as you did in post #1, like this:
$$F_X(x) = \begin{cases} 0 &\text{if $x < 1$}\\
(x-1)^2 & \text{if $1 \leq x < 2$}\\
1 & \text{if $x \geq 2$}
\end{cases}
$$
 
Last edited:

1. What is the expected value of max{Y_1,Y_2}?

The expected value of max{Y_1,Y_2} is the average value that we would expect to obtain if we repeatedly took the maximum value between two independent random variables, Y_1 and Y_2. It is calculated by taking the sum of the products of each possible outcome and their respective probabilities.

2. How is the expected value of max{Y_1,Y_2} different from the expected values of Y_1 and Y_2 separately?

The expected value of max{Y_1,Y_2} takes into account the maximum of the two random variables, while the expected values of Y_1 and Y_2 separately only consider the individual random variables. The expected value of max{Y_1,Y_2} is usually greater than or equal to the expected values of Y_1 and Y_2 separately.

3. What is the variance of max{Y_1,Y_2}?

The variance of max{Y_1,Y_2} is a measure of how spread out the values of the maximum of two random variables are from the expected value. It is calculated by taking the sum of the squared deviations from the expected value, weighted by their respective probabilities.

4. How is the variance of max{Y_1,Y_2} related to the variances of Y_1 and Y_2 separately?

The variance of max{Y_1,Y_2} is not directly related to the variances of Y_1 and Y_2 separately. However, if the two random variables are independent, the variance of max{Y_1,Y_2} can be calculated by taking the maximum of the variances of Y_1 and Y_2.

5. Can the expected value and variance of max{Y_1,Y_2} be calculated for any two random variables?

Yes, the expected value and variance of max{Y_1,Y_2} can be calculated for any two random variables, as long as they are independent. However, the calculations may be more complex for certain types of random variables and may require advanced statistical techniques.

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