Verifying Stochastic Variable Result: Urgent Homework

In summary, the conversation is about a problem involving a stochastic variable Y with a given distribution function and the task of proving its absolute continuity and finding its density function. Part one of the solution correctly applies a theorem to show absolute continuity and finds the density function to be cos(y). In part two, the solution correctly uses the given density function to find the probability of a given interval and suggests adding more explanation and justification to make the solution easier to understand. The conversation concludes with a request for feedback on the solutions and a reminder to cite sources.
  • #1
Beowulf2007
17
0

Homework Statement




Dear All,

I have this problem here.

Part(1)

Let Y be a stochastic variable with the distribution function [tex]F_{Y}[/tex] given by:

[tex]P(Y \leq y) = F_{Y}(y) = \left\{ \begin{array}{ccc} \ 0& \ \ \mathrm{if} \ y < 0 \\ sin(y)& \ \ \mathrm{if} \ y \in [0,\pi/2] \\ 1& \ \ \mathrm{if} \ y > 0. \end{array}[/tex]

Explain why Y is absolute continious and give the density [tex]f_{Y}.[/tex]


The Attempt at a Solution



Proof

Using the following theorem:

Let X be a stochastic variable with the distribution function F, Assuming that F is continuous and that F' exists in all but finite many points [tex]x_{1} < x_{2} < x_\ldots < x_{n}[/tex]. Then X is absolutely continuous with the desensity

[tex]f(x) = \left\{ \begin{array}{ccc} F'(x) \ \ &\mathrm{if} \ \ x \notin \{x_{1}, x_{2}, \ldots, x_{n} \} \\ 0 \ \ &\mathrm{if} \ \ x \in \{x_{1}, x_{2}, \ldots, x_{n} \}. \end{array}[/tex]

By the theorem above its clearly visable that [tex]F_Y[/tex] is continuous everywhere by the definition of continouty, then F' exists and thusly

[tex]f_{Y} = \frac{d}{dy}(sin(y)) = cos(y).[/tex]


Therefore Y is absolute continious.


Part two

Let X be a absolute continuous stochastic variable with the probability density [tex]f_{X}[/tex] given by

[tex]f_{X}(x) = \left\{ \begin{array}{ccc} \frac{1}{9}|x|& \ \ \mathrm{if} \ \ x \in ]-3,3[ \\ 0& \ \ \mathrm{otherwise.} \end{array}[/tex]

Show that [tex]P(|X| \leq 1) = \frac{1}{9}.[/tex]

Proof

Since we know that the density function is given according to the definition

[tex]\int_{-\infty}^{\infty} f(x) dx = \int_{-3}^{3} \frac{1}{9}|x| dx = 1[/tex] Then to obtain where [tex]P(|X| \leq 1)[/tex] we analyse the interval

[tex]x \in \{-1,1\}[/tex] from which we obtain

[tex]P(|X| \leq 1) = \int_{-1}^{1} \frac{1}{9}|x| dx = \frac{1}{9} \cdot \int_{-1}^{1} |x| dx = [\frac{x \cdot |x|}{18}]_{x=-1}^{1} = \frac{1}{9}.[/tex]


How does part one and two look? Do I need to add more text if yes what?

The problem is correctly formulated from my textbook.

Thanks in advance.

BR
Beowulf...
 
Last edited:
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  • #2



Dear Beowulf,

Part one looks good. You have correctly applied the theorem to show that Y is absolutely continuous and have found the density function f_Y. However, it would be helpful to explain why the density function is cos(y) and not just state it. You could mention that since sin(y) is the derivative of cos(y), it follows that cos(y) is the density function.

As for part two, your proof is correct but it would be helpful to explain why the interval [-1,1] is used and how you obtained it. You could also mention that the interval [-3,3] is chosen because it is the support of the density function f_X.

Overall, your solutions are well-written and clear. However, it would be good to add more explanation and justification to make them more understandable to someone who is not familiar with the problem. Also, it would be helpful to cite your sources for the theorems and definitions used.

Hope this helps!




Scientist
 

1. What is a stochastic variable?

A stochastic variable is a random variable that can take on different values with a certain probability distribution. It is used to model uncertain or random events in statistical analysis.

2. Why is it important to verify stochastic variable results?

Verifying stochastic variable results is important because it ensures the accuracy and reliability of the data. It allows scientists to validate their findings and make informed decisions based on the results.

3. How do you verify stochastic variable results?

Stochastic variable results can be verified through various methods such as statistical tests, simulations, and sensitivity analysis. These methods help to assess the consistency and robustness of the results.

4. What are some common challenges in verifying stochastic variable results?

Some common challenges in verifying stochastic variable results include dealing with large and complex datasets, selecting appropriate statistical tests, and accounting for potential sources of error or bias in the data.

5. What are the implications of not verifying stochastic variable results?

If stochastic variable results are not verified, it can lead to incorrect conclusions and decisions being made based on unreliable data. This can have serious consequences in fields such as healthcare, finance, and environmental science.

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