How can we calculate the probability?

  • Context: MHB 
  • Thread starter Thread starter mathmari
  • Start date Start date
  • Tags Tags
    Probability
Click For Summary

Discussion Overview

The discussion revolves around calculating probabilities related to random variables, specifically focusing on the distribution functions of discrete and continuous random variables. Participants explore the calculations of probability functions for given random variables and address potential issues in their reasoning.

Discussion Character

  • Mathematical reasoning
  • Debate/contested
  • Technical explanation

Main Points Raised

  • Participants discuss the calculation of the distribution function \( F_X \) for a random variable \( X \) and the subsequent probability function \( p_Y \) for \( Y = |X| \).
  • Some participants propose that \( p_Y(y) = P(Y(\omega) = y) = P(|X(\omega)| = y) = P(X(\omega) = y \lor X(\omega) = -y) \) for \( y \geq 0 \).
  • There is uncertainty regarding the correct probabilities for \( p_Y(0) \), \( p_Y(4) \), and \( p_Y(12) \), with some suggesting \( p_Y(4) \) might equal \( \frac{1}{2} \) instead of \( \frac{1}{4} \).
  • Participants analyze the distribution function \( F_Z \) for a continuous random variable \( Z \) and discuss the implications of differentiability and the use of the Dirac delta function.
  • There is a debate over the completeness and correctness of the steps taken to calculate probabilities, particularly in relation to continuous random variables.

Areas of Agreement / Disagreement

Participants express differing views on the correct probabilities for the random variables discussed, particularly \( p_Y(4) \). The discussion on the continuous random variable \( Z \) also reveals uncertainty about how to properly express its probability function. Overall, there is no clear consensus on several points raised.

Contextual Notes

Some calculations rely on assumptions about the distributions and may not account for all conditions or definitions of the random variables involved. The discussion highlights the complexity of transitioning between discrete and continuous probability functions.

mathmari
Gold Member
MHB
Messages
4,984
Reaction score
7
Hey! :giggle:

The distribution of a random variable $X:\Omega\rightarrow \mathbb{R}$ is given by the probability function $p_X$ as follows:
1636058792394.png


(i) Calculate the distribution function $F_X$ of $X$.
(ii) Let $Y(\omega)=|X(\omega)|$ for all $\omega\in \Omega$. Determine $p_Y$. I have done the following :

(i) \begin{align*}&F_X(-4)=p_X(-4)=\frac{1}{4} \\ &F_X(0)=p_X(-4)+p_X(0)=\frac{1}{4}+\frac{1}{6}=\frac{5}{12} \\ &F_X(4)=p_X(-4)+p_X(0)+p_X(4)=\frac{1}{4}+\frac{1}{6}+\frac{1}{4}=\frac{5}{12}+\frac{1}{4}=\frac{2}{3} \\ &F_X(12)=p_X(-4)+p_X(0)+p_X(4)+p_X(12)=\frac{1}{4}+\frac{1}{6}+\frac{1}{4}+\frac{1}{3}=\frac{2}{3}+\frac{1}{3}=1\end{align*}

(ii) We have that $Y(\Omega)\in \{0, 4, 12\}$, right? But how can we calculate the probability? :unsure:
 
Physics news on Phys.org
mathmari said:
(ii) We have that $Y(\Omega)\in \{0, 4, 12\}$, right? But how can we calculate the probability?

Hey mathmari!

Don't we have for $y\ge 0$ that $p_Y(y)=P(Y(\omega)=y)=P(|X(\omega)|=y)=P(X(\omega)=y \lor X(\omega)=-y)$? 🤔

Btw, we have for $\omega\in \Omega$ that $Y(\omega)\in \{0, 4, 12\}$.
However $Y(\Omega)= \{0, 4, 12\}$. (Nerd)
 
Klaas van Aarsen said:
Don't we have for $y\ge 0$ that $p_Y(y)=P(Y(\omega)=y)=P(|X(\omega)|=y)=P(X(\omega)=y \lor X(\omega)=-y)$? 🤔

Btw, we have for $\omega\in \Omega$ that $Y(\omega)\in \{0, 4, 12\}$.
However $Y(\Omega)= \{0, 4, 12\}$. (Nerd)

So we get $$p_Y(0)=\frac{1}{6}, \ p_Y(4)=\frac{1}{4}, \ p_Y(12)=\frac{1}{3}$$ right? :unsure:
 
mathmari said:
So we get $$p_Y(0)=\frac{1}{6}, \ p_Y(4)=\frac{1}{4}, \ p_Y(12)=\frac{1}{3}$$ right?

They should sum up to 1...
It seems we missed a chance somewhere. (Worried)
 
Klaas van Aarsen said:
They should sum up to 1...
It seems we missed a chance somewhere. (Worried)

Do we maybe have the following :
$$p_Y(4)=P(X(\omega)=4 \lor X(\omega)=-4)=P(X(\omega)=4) + P(X(\omega)=-4)=\frac{1}{4}+\frac{1}{4}=\frac{2}{4}=\frac{1}{2}$$
:unsure:
 
mathmari said:
Do we maybe have the following :
$$p_Y(4)=P(X(\omega)=4 \lor X(\omega)=-4)=P(X(\omega)=4) + P(X(\omega)=-4)=\frac{1}{4}+\frac{1}{4}=\frac{2}{4}=\frac{1}{2}$$
Yep. (Nod)
 
Klaas van Aarsen said:
Yep. (Nod)

So for all probabilities we have :
\begin{align*}p_Y(0)&=P(Y(\omega)=0)=P(|X(\omega)|=0)=P(X(\omega)=0 \lor X(\omega)=-0)=P(X(\omega)=0)\\ & = \frac{1}{6} \\
p_Y(4)&=P(Y(\omega)=4)=P(|X(\omega)|=4)=P(X(\omega)=4 \lor X(\omega)=-4)=P(X(\omega)=4) + P(X(\omega)=-4)\\ & =\frac{1}{4}+\frac{1}{4}=\frac{2}{4}=\frac{1}{2} \\
p_Y(12)&=P(Y(\omega)=12)=P(|X(\omega)|=12)=P(X(\omega)=12 \lor X(\omega)=-12)\\ & =P(X(\omega)=12) + P(X(\omega)=-12)=\frac{1}{3}+0=\frac{1}{3}\end{align*}
right? :unsure:
 
Yep. (Nod)

And they sum up to 1 now as they should.(Emo)
 
Great! (Clapping)At the next subquestion we have :
Let $Z : \Omega \rightarrow \mathbb{R}$ be a random variable with distribution function $F_Z : \mathbb{R} \rightarrow [0, 1]$,
1636117560405.png


(i) Calculate $p_Z$.
(ii) Calculate $P[2 \leq Z < 3]$.I have done the following :

(i) \begin{align*}&p_Z(1)=F_Z(1)=\frac{2}{5} \\ &p_Z(2)=F_Z(2)-F_Z(1)=\frac{3}{5}-\frac{2}{5}=\frac{1}{5} \\ &p_Z\left (\frac{5}{2}\right )=F_Z\left (\frac{5}{2}\right )-F_Z(2)=\frac{9}{10}-\frac{3}{5}=\frac{9}{10}-\frac{6}{10}=\frac{3}{10} \\ &p_Z(3)=F_Z(3)-F_Z\left (\frac{5}{2}\right )=1-\frac{9}{10}=\frac{1}{10}\end{align*}

(ii) \begin{equation*}P[2\leq Z<3]=p_Z(2)=F_Z(2)-F_Z(1)=\frac{3}{5}-\frac{2}{5}=\frac{1}{5}\end{equation*} Is everything correct and complete? :unsure:
 
Last edited by a moderator:
  • #10
$Z$ is a continuous random variable now, which means we need to specify $p_Z$ for every real number.
What is for instance $p_Z(1.5)$? (Wondering)
 
  • #11
Klaas van Aarsen said:
$Z$ is a continuous random variable now, which means we need to specify $p_Z$ for every real number.
What is for instance $p_Z(1.5)$? (Wondering)

Do you mean that we have to write :
\begin{align*}&p_Z(x)=F_Z(1)=\frac{2}{5} \ \text{ for } 1\leq x<2 \\ &p_Z(x)=F_Z(2)-F_Z(1)=\frac{3}{5}-\frac{2}{5}=\frac{1}{5} \ \text{ for } 2\leq x<\frac{5}{2} \\ &p_Z\left (x\right )=F_Z\left (\frac{5}{2}\right )-F_Z(2)=\frac{9}{10}-\frac{3}{5}=\frac{9}{10}-\frac{6}{10}=\frac{3}{10} \ \text{ for } \frac{5}{2}\leq x<3 \\ &p_Z(x)=F_Z(3)-F_Z\left (\frac{5}{2}\right )=1-\frac{9}{10}=\frac{1}{10} \ \text{ for } x>3 \end{align*} Or what do we do in this case? :unsure:
 
  • #12
mathmari said:
Do you mean that we have to write :
\begin{align*}&p_Z(x)=F_Z(1)=\frac{2}{5} \ \text{ for } 1\leq x<2 \\ &p_Z(x)=F_Z(2)-F_Z(1)=\frac{3}{5}-\frac{2}{5}=\frac{1}{5} \ \text{ for } 2\leq x<\frac{5}{2} \\ &p_Z\left (x\right )=F_Z\left (\frac{5}{2}\right )-F_Z(2)=\frac{9}{10}-\frac{3}{5}=\frac{9}{10}-\frac{6}{10}=\frac{3}{10} \ \text{ for } \frac{5}{2}\leq x<3 \\ &p_Z(x)=F_Z(3)-F_Z\left (\frac{5}{2}\right )=1-\frac{9}{10}=\frac{1}{10} \ \text{ for } x>3 \end{align*} Or what do we do in this case?

It's a bit strange really.
We have $F_Z(z) = \int_{-\infty}^z p_Z(x)\,dx \implies p_Z(x) = F_Z'(x)$.
That means that $p_Z(x)=0$ for $1<x<2$.
However, $F_Z(x)$ is not differentiable at $x=1$, so we would need to introduce the Dirac delta function to describe $p_Z(x)$ there. 🤔
 
Last edited:
  • #13
Klaas van Aarsen said:
It's a bit strange really.
We have $F_Z(z) = \int_{-\infty}^z p_Z(x)\,dx \implies p_Z(x) = F_Z'(x)$.
That means that $p_Z(x)=0$ for $1<x<2$.
However, $F_Z(x)$ is not differentiable at $x=1$, so we would need to introduce that Dirac delta function to describe $p_Z(x)$ there. 🤔

Is this related to the below example?

1636123413637.png


:unsure:
 
  • #14
mathmari said:
Is this related to the below example?
Yes. That example shows $p_X$ as a discrete function and $F_X$ as a continuous function.
If we follow that example, then I think that what you wrote before for $p_Z$ as a discrete function is correct. 🤔
 
  • #15
Klaas van Aarsen said:
Yes. That example shows $p_X$ as a discrete function and $F_X$ as a continuous function.
If we follow that example, then I think that what you wrote before for $p_Z$ as a discrete function is correct. 🤔

Do you mean what I wrote in post #9 or in post #11 ? :unsure:
 
  • #16
mathmari said:
(ii) \begin{equation*}P[2\leq Z<3]=p_Z(2)=F_Z(2)-F_Z(1)=\frac{3}{5}-\frac{2}{5}=\frac{1}{5}\end{equation*}

I wrote all steps analytically as follows :
\begin{align*}P[2\leq Z<3]&=P[\{Z<3\}\setminus \{Z<2\}]=P[Z<3]-P[Z<2] \\ &=P[\{Z\leq 3\}\setminus \{Z=3\}]-P[\{Z\leq 2\}\setminus \{Z=2\}]\\ & =\left (P[Z\leq 3]-P[Z=3]\right )-\left (P[Z\leq 2]-P[Z=2]\right ) \\ &=\left (F_Z(3)-P[Z=3]\right )-\left (F_Z(2)-P[Z=2]\right )\\ &=\left (F_Z(3)-p_Z(3)\right )-\left (F_Z(2)-p_Z(2)\right )\\ &=\left (1-\frac{1}{10}\right )-\left (\frac{3}{5}-\frac{1}{5}\right )\\ &=1-\frac{1}{10}-\frac{3}{5}+\frac{1}{5}\\ & =\frac{1}{2}
\end{align*}
Are all steps correct? :unsure:
 
  • #17
mathmari said:
Do you mean what I wrote in post #9 or in post #11 ?
Post #9. 🤔

mathmari said:
I wrote all steps analytically as follows :
\begin{align*}P[2\leq Z<3]&=P[\{Z<3\}\setminus \{Z<2\}]=P[Z<3]-P[Z<2] \\ &=P[\{Z\leq 3\}\setminus \{Z=3\}]-P[\{Z\leq 2\}\setminus \{Z=2\}]\\ & =\left (P[Z\leq 3]-P[Z=3]\right )-\left (P[Z\leq 2]-P[Z=2]\right ) \\ &=\left (F_Z(3)-P[Z=3]\right )-\left (F_Z(2)-P[Z=2]\right )\\ &=\left (F_Z(3)-p_Z(3)\right )-\left (F_Z(2)-p_Z(2)\right )\\ &=\left (1-\frac{1}{10}\right )-\left (\frac{3}{5}-\frac{1}{5}\right )\\ &=1-\frac{1}{10}-\frac{3}{5}+\frac{1}{5}\\ & =\frac{1}{2}
\end{align*}
Are all steps correct?
Correct although I believe it suffices to write:
\begin{align*}P[2\leq Z<3]= P(Z<3)-P(Z<2) =\lim_{x\to 3^-} F_Z(x) - \lim_{x\to 2^-} F_Z(x) = \frac 9{10}-\frac 25 =\frac{1}{2}
\end{align*}
🤔
 
  • #18
Klaas van Aarsen said:
Post #9. 🤔Correct although I believe it suffices to write:
\begin{align*}P[2\leq Z<3]= P(Z<3)-P(Z<2) =\lim_{x\to 3^-} F_Z(x) - \lim_{x\to 2^-} F_Z(x) = \frac 9{10}-\frac 25 =\frac{1}{2}
\end{align*}
🤔

Ah ok! Thank you very much! (Sun)
 

Similar threads

  • · Replies 5 ·
Replies
5
Views
1K
  • · Replies 2 ·
Replies
2
Views
2K
  • · Replies 1 ·
Replies
1
Views
2K
  • · Replies 1 ·
Replies
1
Views
2K
  • · Replies 4 ·
Replies
4
Views
2K
  • · Replies 7 ·
Replies
7
Views
962
  • · Replies 1 ·
Replies
1
Views
2K
  • · Replies 4 ·
Replies
4
Views
2K
  • · Replies 11 ·
Replies
11
Views
3K
Replies
1
Views
3K