Understanding the CDF and PDF of a Uniform Distribution for Y

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Discussion Overview

The discussion revolves around the cumulative distribution function (CDF) and probability density function (PDF) of a uniform distribution for a random variable Y, defined in terms of another variable X. Participants explore the relationships between these functions, particularly in the context of specific values and intervals.

Discussion Character

  • Exploratory
  • Technical explanation
  • Mathematical reasoning
  • Debate/contested

Main Points Raised

  • One participant outlines the definitions of Y based on the value of X, stating that for X>3, Y=6-X and for X<3, Y=X.
  • Another participant confirms the calculations for P(Y>y) and suggests that the CDF can be derived from it using the relationship P(Yy).
  • There is a proposal that the PDF of Y is 1/3 for the interval 0≤y<3, indicating a uniform distribution.
  • A participant questions the notation used for the inequalities in the expression for P(Y>y), considering whether strict inequalities should be used instead of non-strict ones.
  • Clarifications are provided regarding the continuity of the CDF and the presence of discontinuities in the PDF at specific points.

Areas of Agreement / Disagreement

Participants generally agree on the calculations and relationships between the CDF and PDF, but there is some debate regarding the use of strict versus non-strict inequalities in the definitions of P(Y>y). The discussion remains unresolved on this specific notation issue.

Contextual Notes

Participants note that the CDF is continuous at the points y=0 and y=3, while the PDF exhibits jump discontinuities at these points. There is an acknowledgment of potential ambiguity in mathematical notation regarding inequalities.

lemonthree
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I need guidance on part c, finding the cdf/pdf of Y.

I understand that for X>3, Y=6-X and for X<3, Y=X.
For X = 3, Y=3

For part b, I got P(Y>y)= (3-y)/3, for 0≤y<3

Now for part c, I know P(Y>y) relates to the cdf.
But the definition of cdf relates to P(Y<y), so I'm guessing I have to
do 1-P(Y>y) to get the cdf which is y/3, 0≤y<3.

I'm thinking the pdf would be 1/3 for 0≤y<3?

I know for sure Y is a uniform distribution.
I'm not too sure on the interval (x-a)/(b-a)
Is it Y~Uniform distribution(0,3)?
question.jpg
 
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Hi lemonthree,

The short answer to your post is that you're basically correct on everything you wrote. This response is really to help clean up some of the details. Please refer to the image below, which is a plot of the random variable $Y$ as a function of $X$, as defined by $Y = \min\{X, 6-X\}$.

For completeness in part (b), the values for $P(Y>y)$ should be included for $y\leq 0$ and $y\geq 3$. From the graph below we see that

$P(Y > y) = \begin{cases}
1 & y\leq 0\\
1-\frac{y}{3} & 0\leq y\leq 3\\
0 & y\geq 3
\end{cases}$

For part (c) you can certainly use $P(Y<y) = 1-P(Y>y)$ and the formula from part (b) to get

$P(Y < y) = \begin{cases}
0 & y\leq 0\\
\frac{y}{3} & 0\leq y\leq 3\\
1 & y\geq 3
\end{cases}$

Another possibility is to reason geometrically. For example, if $y = 1$ (as shown in the figure), we can see that $P(Y < 1) = P(X<1\,\text{or}\, X>5) = 2\cdot P(X <1) = 1/3,$ where the second equality is true because the graph is symmetric about the vertical line $X = 3.$ This same argument can be used for any $y$ such that $0\leq y\leq 3$; i.e., $P(Y<y) = P(X<y\,\text{or}\, X>6-y) = 2\cdot P(X<y) = \frac{2y}{6}=\frac{y}{3}$ for all $0\leq y\leq 3$.

desmos-graph (1).png


The CDF is pictured below. The PDF is obtained by taking the derivative of the CDF. I suspect you're familiar with derivatives. If not, derivative means the slope of a graph. Hence, when we say the PDF is the derivative of the CDF, we mean we get the PDF by looking at the slopes of the CDF. Because there are sharp corners in the graph of the CDF, it is technically not differentiable at these points, which results in so-called "jump discontinuities" in the PDF. In any case, the resulting PDF is given by

$f(t) = \begin{cases}
0 & t< 0\\
\frac{1}{3} & 0\leq t\leq 3\\
0 & t> 3
\end{cases}$

desmos-graph (2).png
 
Last edited:
Thank you so much GJA. That was very helpful. I just have a question on this part regarding the inequality signs.

GJA said:
For completeness in part (b), the values for $P(Y>y)$ should be included for $y\leq 0$ and $y\geq 3$. From the graph below we see that

$P(Y > y) = \begin{cases}
1 & y\leq 0\\
1-\frac{y}{3} & 0\leq y\leq 3\\
0 & y\geq 3
\end{cases}$

Should it be
$P(Y > y) = \begin{cases}
1 & y\ < 0\\
1-\frac{y}{3} & 0\leq y\leq 3\\
0 & y\ > 3
\end{cases}$
instead? Or both ways work fine? Although the values are the same I'm not very sure whether I'm mathematically correct...
 
Great question, and glad to hear the post was helpful.

Since the values are the same, both answers are acceptable. Because the values are the same, the CDF is a "continuous" function; meaning there aren't jumps/different values at the points $y=0$ and $y=3$. For comparison, the PDF is not continuous at $y=0$ and $y=3$. This can be seen as jumps in the graph below. For the PDF, you can see that we used strict inequalities to define $f(t)$.

desmos-graph(3).png
 
Ah ok, that makes sense. Thank you so much for your help!
 

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