Find the probability distribution

In summary: I think you are right, it should be 2/9 (x+1) and not 2/9 (x-1). In summary, to find the pdf of Y = X^2, we need to find the cdf of Y by integrating the given pdf, 2/9 (x+1), from -\sqrt{y} to \sqrt{y}. However, we should also take into consideration the range of y, which is 1 \leq y \leq 4. Therefore, the correct cdf is -4\sqrt{y} for y>1.
  • #1
relinquished™
79
0
Given the probability distribution function

[tex]

f(x) = \frac{2}{9}(x-1), -1<x<2

[/tex]

find the pdf of [tex] Y = X^2 [/tex]

My Solution:

When x = -1, y = 1 and when x = 2, y = 4, so the range of y is

[tex]

1 \leq y \leq 4

[/tex]

So to find the pdf of Y = X^2, we need to find the cdf of Y. Since Y is nontrivial over the interval [tex] 1 \leq y \leq 4 [/tex],

[tex]

F(y) = P(1 \leq Y \leq y)
=P(1 \leq x^2 \leq y)

[/tex]

I'm at a loss here. I do not know how I should deal with square rooting the x, since [tex] x^2 \leq y [/tex] is rewritten as [tex] -\sqrt{y} \leq x \leq \sqrt{y}[/tex]

Any suggestions?
 
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  • #2
What you have is correct: [itex]-\sqrt{y}\leqx\leq\sqrt{y}[/itex]. Now integrate your pdf for x, (2/9)(x-1) from -y to y (be careful about y> 1!).
 
  • #3
err... when you mean about be careful of y>1, do you mean that I have to separate the integral like this:

[tex]

\int^{1}_{-\sqrt{y}} f(x)dx + \int^{\sqrt{y}}_{1} f(x)dx

[/tex]

Because I know that y=1 should not be within the range of y (since y is just greater than 1)

Edit:

I got a cdf of [tex]-4\sqrt{y} [/tex]. I am sure I did something wrong and it must have something to do with that y>1 precaustion...
 
Last edited:
  • #4
Hello relinquished! Isn't it that it should be 2/9 (x + 1) as the given?
 
  • #5
well... if the pdf really is [tex] \frac{2}{9}(x+1) [/tex] then I should look back at the book ^^;
 
  • #6
I don't think it is found in the book.
 

1. What is a probability distribution?

A probability distribution is a mathematical function that describes the likelihood of different outcomes in a random event. It shows the range of possible values and their corresponding probabilities.

2. How is a probability distribution calculated?

A probability distribution is calculated by dividing the number of desired outcomes by the total number of possible outcomes. This gives the probability of a single event occurring. To find the probability distribution for multiple events, you would need to use more advanced statistical techniques.

3. What is the difference between discrete and continuous probability distributions?

A discrete probability distribution is one where the possible outcomes are countable and finite, such as rolling a dice. A continuous probability distribution is one where the possible outcomes are uncountable and infinite, such as the height of individuals in a population.

4. How can probability distributions be used in real life?

Probability distributions are used in a variety of fields, such as finance, medicine, and engineering. They can be used to analyze data, make predictions, and make decisions based on the likelihood of certain outcomes.

5. What is the purpose of finding a probability distribution?

The purpose of finding a probability distribution is to better understand the likelihood of different outcomes in a random event. This can help in making informed decisions and making predictions based on data. It also allows for the calculation of important statistical measures such as mean, variance, and standard deviation.

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