What Does P(X ∈ dx) Mean in Probability Notation?

In summary: Hope that helps. Hmm, books?Well, I guess that would be any book where probability is explained in combination with calculus.
  • #1
gnob
11
0
Good day!
I was trying to make sense of the notation $P(X \in dx),$ where $X$ is a continuous random variable. Some also write this one as $P(X \in [x, x+dx])$ to represent the probability that the random variable $X$ takes on values in the interval $[x, x+dx].$

I have seen similar notation a lot in my readings such as the ff:
$$
P(Z_v \in dy) = \frac{1}{\Gamma(v)}e^{-y}y^{v-1} dy \quad\quad \text{and}\quad\quad
P\left( \int_0^{\tau} e^{\sigma B_s - p\sigma^2 s/2} ds \in du,\,\, B_{\tau} \in dy\right).
$$

Please help me understand these notations, or better yet please suggest me a (reference) book that rigorously explains these notations?
Thanks in advance.
 
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  • #2
gnob said:
Good day!
I was trying to make sense of the notation $P(X \in dx),$ where $X$ is a continuous random variable. Some also write this one as $P(X \in [x, x+dx])$ to represent the probability that the random variable $X$ takes on values in the interval $[x, x+dx].$

I have seen similar notation a lot in my readings such as the ff:
$$
P(Z_v \in dy) = \frac{1}{\Gamma(v)}e^{-y}y^{v-1} dy \quad\quad \text{and}\quad\quad
P\left( \int_0^{\tau} e^{\sigma B_s - p\sigma^2 s/2} ds \in du,\,\, B_{\tau} \in dy\right).
$$

Please help me understand these notations, or better yet please suggest me a (reference) book that rigorously explains these notations?
Thanks in advance.

Welcome to MHB, gnob! :)

As far as I'm concerned $P(X \in dx)$ is bad notation.
According to your explanation it refers to an $x$, but that $x$ is not part of the notation, which is bad.

A more usual notation is $P(X = x)dx$ which is the same as $P(x \le X < x + dx)$.
We're talking about a probability density here, which is the probability that an event occurs in a (very) small interval.
Usually, you'd use a probability density to define a probability between 2 boundaries.
Like:
$$P(a \le X < b) = \int_a^b P(X=x)dx$$
 
  • #3
I like Serena said:
Welcome to MHB, gnob! :)

As far as I'm concerned $P(X \in dx)$ is bad notation.
According to your explanation it refers to an $x$, but that $x$ is not part of the notation, which is bad.

A more usual notation is $P(X = x)dx$ which is the same as $P(x \le X < x + dx)$.
We're talking about a probability density here, which is the probability that an event occurs in a (very) small interval.
Usually, you'd use a probability density to define a probability between 2 boundaries.
Like:
$$P(a \le X < b) = \int_a^b P(X=x)dx$$

Thanks for your time and reply. Its really of great help.
Though I want to ask if you know of some books, that discusses the above topic.
Thanks a lot.
 
  • #4
gnob said:
Thanks for your time and reply. Its really of great help.
Though I want to ask if you know of some books, that discusses the above topic.
Thanks a lot.

Hmm, books?
Well, I guess that would be any book where probability is explained in combination with calculus.
Sorry, but I don't have any book in particular in mind.
 
  • #5


Hello,

The notation $P(X \in dx)$ or $P(X \in [x, x+dx])$ represents the probability of a continuous random variable $X$ falling within a very small interval $dx$ around a particular value $x$. This notation is commonly used in probability and statistics to represent the probability distribution of a continuous random variable.

In your examples, the first notation $P(Z_v \in dy)$ represents the probability of a random variable $Z_v$ falling within a small interval $dy$, where $Z_v$ follows a Gamma distribution with shape parameter $v$. The second notation $P\left( \int_0^{\tau} e^{\sigma B_s - p\sigma^2 s/2} ds \in du,\,\, B_{\tau} \in dy\right)$ represents the joint probability of a random variable $B_{\tau}$ falling within a small interval $dy$ and the integral of a stochastic process $B_s$ falling within a small interval $du$.

To better understand these notations, I would recommend looking into textbooks on probability and statistics, such as "Introduction to Probability" by Joseph K. Blitzstein and Jessica Hwang, or "Mathematical Statistics and Data Analysis" by John A. Rice. These books provide a rigorous explanation of probability notations and concepts. Additionally, online resources such as Khan Academy and Coursera offer free courses on probability and statistics that can also help clarify these notations.

I hope this helps and good luck in your studies!
 

Related to What Does P(X ∈ dx) Mean in Probability Notation?

What is the meaning of "P(X ϵ dx)" in scientific notation?

In scientific notation, "P(X ϵ dx)" represents the probability that a random variable X will fall within a given interval dx. This notation is commonly used in statistics and probability to describe the likelihood of a specific event occurring.

How is "P(X ϵ dx)" calculated?

The calculation of "P(X ϵ dx)" depends on the specific distribution of the random variable X. In general, it involves integrating the probability density function over the interval dx. This can be done using calculus or statistical software.

What is the difference between "P(X ϵ dx)" and "P(X = x)"?

"P(X ϵ dx)" represents the probability of X falling within an interval dx, while "P(X = x)" represents the probability of X taking on a specific value x. The former is a continuous probability distribution, while the latter is a discrete probability distribution.

Why is "P(X ϵ dx)" often used in scientific notation instead of "P(X = x)"?

"P(X ϵ dx)" is often used in scientific notation because it allows for more flexibility in describing the probability of an event. It can also be used to describe the probability of a range of values, rather than a single value. Additionally, many real-world phenomena can be better modeled using continuous probability distributions.

What are some common examples of using "P(X ϵ dx)" in scientific research?

"P(X ϵ dx)" is commonly used in scientific research to describe the likelihood of a continuous variable falling within a specific range. For example, it may be used to calculate the probability of a specific range of temperatures occurring in a given location, or the probability of a certain number of radioactive particles decaying within a specific time interval.

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