What is the cdf of the area of a square with a uniform distribution over (0, 5)?

In summary, the cumulative distribution function for the area of a square, Y, can be found by first finding the cdf of the side, X, and then taking the square root of 0.2 times x. It is important to note that the cdf takes the value of 0 for x less than 0 and 1 for x greater than 25.
  • #1
theloathedone
18
0

Homework Statement


Let the random variable X represent the length of the side of a square. It has a uniform distribution over the interval (0, 5).

What is the cumulative distribution function for the area of the square, Y?


Homework Equations


F(x) = 0.2x (the cdf of the side).


The Attempt at a Solution


So I tried simply squaring F(x), giving 0.04x^2, which is incorrect since F(25) = 25 instead of 1. Also, it wouldn't make sense for the probability of the largest areas to have the highest probability, since:
P(4.9 < X < 5.0) = 0.02
Therefore P(4.9^2 < X < 5.0^2) = 0.02
But going by 0.04x^2 we get 0.08 or something.

Also, I couldn't find anything like this in my textbook (I'm a high school student), is there any good website to line this stuff from?

Thanks in advance.
 
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  • #2
theloathedone said:

Homework Statement


Let the random variable X represent the length of the side of a square. It has a uniform distribution over the interval (0, 5).

What is the cumulative distribution function for the area of the square, Y?

Homework Equations


F(x) = 0.2x (the cdf of the side).

The Attempt at a Solution


So I tried simply squaring F(x), giving 0.04x^2, which is incorrect since F(25) = 25 instead of 1. Also, it wouldn't make sense for the probability of the largest areas to have the highest probability, since:
P(4.9 < X < 5.0) = 0.02
Therefore P(4.9^2 < X < 5.0^2) = 0.02
But going by 0.04x^2 we get 0.08 or something.

Also, I couldn't find anything like this in my textbook (I'm a high school student), is there any good website to line this stuff from?

Thanks in advance.

No, why are you squaring F(x)?

To handle this type of problem, we often try to find the cdf of S first, then (if the problem asks further for pdf function) we can obtain it by differentiating the cdf of S.

So, it goes like this:
[tex]\begin{align*}F_S(x) = P(S \le x) = P(X^2 \le x) &= \left\{ \begin{array}{ll} 0 & , \mbox{ if } x \le 0 \\ P(-\sqrt{x} \le X \le \sqrt{x}) & , \mbox{ if } x > 0 \end{array} \right. \\
&= \left\{ \begin{array}{ll} 0 & , \mbox{ if } x \le 0 \\ P(-\sqrt{x} \le X \le 0) + P(0 < X \le \sqrt{x}) & , \mbox{ if } x > 0 \end{array} \right. \\
&= ...
\end{align}[/tex]

Can you go from here, :)
 
Last edited:
  • #3
You are going the wrong way. In order that [itex]x^2< a[/itex], we must have [itex]x<\sqrt{a}[/itex]. Take the square root of 0.2x, not the square!
 
  • #4
Ah I see where I went wrong.

But it should be [itex]0.2\sqrt{x}[/itex] and not [itex]\sqrt{0.2x}[/itex] right?

Thanks for the speedy responses!
 
  • #5
theloathedone said:
Ah I see where I went wrong.

But it should be [itex]0.2\sqrt{x}[/itex] and not [itex]\sqrt{0.2x}[/itex] right?

Thanks for the speedy responses!

Yup, that's correct. Congratulations. :)

But, remember that [itex]F_S(x) = 0.2\sqrt{x}[/itex] on the interval (0; 25), it takes other values elsewhere.
 
  • #6
yup. it's 0 for x < 0 and 1 for x > 25. Thanks for the help :)
 

Related to What is the cdf of the area of a square with a uniform distribution over (0, 5)?

What does it mean to "square a random variable"?

Squaring a random variable means taking each value of the random variable, multiplying it by itself, and then finding the average of all of those squared values.

Why would I want to square a random variable?

Squaring a random variable is often done in statistical analysis to find the variance of the random variable. This is important for understanding the spread or variability of the data.

What is the difference between squaring a random variable and multiplying it by a constant?

The result of squaring a random variable is a new random variable, while multiplying by a constant simply changes the scale of the original random variable.

Can any random variable be squared?

Yes, any random variable can be squared. However, the result may not always be meaningful or useful in the context of the data being analyzed.

Is squaring a random variable the same as taking the square root of the variance?

No, squaring a random variable and taking the square root of the variance are two different operations. Squaring a random variable results in a new random variable, while taking the square root of the variance results in a single number that represents the spread of the data.

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