Probability of Point Within Radius $x$ from Origin

In summary, the "Probability of Point Within Radius $x$ from Origin" is a measure of the likelihood that a randomly chosen point will fall within a certain distance, $x$, from the origin of a given coordinate system. This probability is often represented by the symbol $P(x)$ and is calculated by dividing the area of a circle with radius $x$ by the total area of the coordinate system. It is important in many fields of science and has practical applications in areas such as physics, statistics, and biology. It is different from other measures of probability, but shares the same fundamental principles and can be used together to solve complex problems.
  • #1
Chris L T521
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Thanks again to those who participated in last week's POTW! Here's this week's problem!

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Problem: A point is uniformly distributed within the disk of radius 1. That is, its density is\[f(x,y)=C,\qquad 0\leq x^2+y^2\leq 1\]
Find the probability that its distance from the origin is less than $x$, $0\leq x\leq 1$.

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Note​: $f(x,y)$ is a density function if $\displaystyle\int_{-\infty}^{\infty} \int_{-\infty}^{\infty} f(x,y)\,dy\,dx = 1$.

 
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  • #2
This week's problem was correctly answered by Ackbach, alphabeta89, and Bacterius; Sudharaka gets honorable mention since he computed the wrong probability... :-/

Here's Ackbach's solution:

First we normalize the function $f(x,y)$ by discovering $C$. We need that
$$\int_{\mathbb{R}} \int_{\mathbb{R}} f(x,y) \, dx \, dy=1,$$
or, switching to polar coordinates, that
$$\int_{0}^{2 \pi} \int_{0}^{1}C \, r \, dr \, d\theta=1.$$
The integral on the LHS is essentially the area, so we have that
$$C= \frac{1}{ \pi r^{2}}= \frac{1}{ \pi},$$
and therefore that
$$f(x,y)= \frac{1}{ \pi}.$$
Next, to find the probability that the point is within a distance of $x$ to the origin, we must
compute the probability
$$P(r<x)= \frac{( \pi x^{2})/ \pi}{( \pi)/ \pi}= x^{2}.$$

Note that I could probably have solved this problem without normalizing, but I felt like doing it.

And here's Bacterius' solution:

Let $\text{X} : (\theta_\text{X}, r_\text{X})$ be a uniformly selected point on the unit circle, in polar coordinates. What is the probability that $r_\text{X} < x$ for some $0 \leq x \leq 1$?

Let us divide the unit circle in concentric rings with inner radius $r$ and thickness $\text{d} r$. What is the total area of all rings up to some radius $x$? We have:

$$A_x = \int_0^x 2 \pi r ~ \text{d} r = \pi x^2$$
This area $A_x$ is the area of the circle of radius $x$ concentric to the unit circle, enclosing all points which have distance less than $x$ to the origin. And the total area of the unit circle is equal to $A = \pi$, so the probability of $\text{X}$ falling inside the area $A_x$ is equal to (this is really a cumulative distribution function):

$$P(r_\text{X} < x) = \frac{A_x}{A} = \frac{\pi x^2}{\pi} = x^2$$
We conclude, that a uniformly selected point on the unit circle has probability $x^2$ to have distance less than $x$ to the origin.​
 

Related to Probability of Point Within Radius $x$ from Origin

What is the "Probability of Point Within Radius $x$ from Origin"?

The "Probability of Point Within Radius $x$ from Origin" is a measure of the likelihood that a randomly chosen point will fall within a certain distance, $x$, from the origin of a given coordinate system. This probability is often represented by the symbol $P(x)$.

How is the "Probability of Point Within Radius $x$ from Origin" calculated?

The calculation of the "Probability of Point Within Radius $x$ from Origin" depends on the distribution of points within the coordinate system. For a uniform distribution, where all points are equally likely to occur, the probability can be calculated by dividing the area of a circle with radius $x$ by the total area of the coordinate system. For other distributions, more complex mathematical formulas may be used.

What is the significance of the "Probability of Point Within Radius $x$ from Origin"?

The "Probability of Point Within Radius $x$ from Origin" is important in many areas of science, including physics, statistics, and computer science. It can be used to model and predict the behavior of systems, such as the movement of particles in a gas or the spread of a disease. It is also a fundamental concept in statistics, where it is used to make inferences and draw conclusions from data.

How does the "Probability of Point Within Radius $x$ from Origin" relate to other measures of probability?

The "Probability of Point Within Radius $x$ from Origin" is a specific type of probability, known as geometric probability. It is different from other measures of probability, such as binomial or normal probability, which are based on discrete or continuous data, respectively. However, all types of probability share the same fundamental principles and can be used together to solve complex problems.

How can the "Probability of Point Within Radius $x$ from Origin" be applied in real-world situations?

The "Probability of Point Within Radius $x$ from Origin" has many practical applications in fields such as engineering, finance, and biology. For example, it can be used to calculate the likelihood of a satellite collision in space or the chance of a stock price falling within a certain range. In biology, it can be used to model the spread of a virus or estimate the chance of a species inhabiting a particular area.

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