Probability density function for a given problem

P= (\frac{2}{\pi}) \sin^{-1}(2/5) \approx .26 ##.In summary, the conversation discusses finding the probability density function of a continuous random variable in a given problem involving a swinging mass on a pendulum. The probability density function is solved for using a normalized equation and then integrated to find the probability of the mass falling into a pond. The final result is approximately 0.26.
  • #1
Maxdenis92
Thread moved from the technical forums, so no Homework Template is shown
https://www.quora.com/How-can-I-find-the-probability-density-function-of-a-continuous-random-variable-in-a-given-problem/answer/Maxime-Denis-2 How can I find the probability density function of a continuous random variable in a given problem?

A mass m swings at the end of a rope (of length L) such as a pendulum above a pond (of half width 2 m) according to a planar oscillation (of amplitude 5m) as depicted in FIG. The branch can break at any time during the cycle. Calculate the probability that the mass will fall to the water as a result of this random break. (Neglect horizontal speed during fall).

I know how to calculate the probability (which is approximately 0.26), but I would like to find a probability density function and the corresponding cumulative distribution function. Excuse-me for my English mistakes. English is my second language.
 
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  • #2
I think this one really belongs in the homework section. Please post homeworks in the homework section in the future and fill out the homework template. ## \\ ## In any case, this one can be written as ## x(t)=A \sin(\omega t) ## where ## \omega=\frac {2 \pi}{T} ##. Basically the density function of the position vs. time can be found by solving for ## t ## : ##\, t=\frac{1}{\omega} \sin^{-1}(x/A)## and finding ## f(x) \Delta x= \Delta t/(T/2) ##. ## f(x) ## is the probability density function for the probability that ## x<X \leq x+\Delta x ##. It is found by taking a derivative which will be found to diverge at ## x=A ## and ## x=-A ##, but the integral from ## x=-A ## to ## x ## where ## -A<x<A ## should be found to converge. For ## x<-A ## and ## x>A ##, ## f(x)=0 ##. To find the probability it lands in the pond, you need to integrate the density function over the limits of the pond. ## \\ ## The forum rules requite the homework helper doesn't give the solution to the problem. Because this one is semi-difficult, I have provided more info than I normally would. I believe what I have provided is correct, and hopefully this is helpful. ## \\ ## Editing: Note: ## T/2 ## is the proper normalization factor. The time the pendulum spends at the different locations is thereby found from this normalized density function. It is only necessary to consider a half cycle of the pendulum, from ## x=-A ## to ## x=A ##.
 
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  • #3
Hello Charles Link. Thank you for your answer. This is not an homework. I just want to know what is the density function and the cumulative distribution function. I know that f(x) must be positive, but f(x) = t(x) = (1/w)arcin(x/A) is not always positive. I don't see what I have to integrate to get the cumulative distribution function. I did it in a probability course, but there was no context. Thank you.
 
  • #4
For ## 0<x<A ## it works ok. The probability density function ## f(x) ## is symmetric about ## x=0 ##. For ## x<0 ##, let ## f(x)=f(-x) ##. ## \\ ## Editing: ## t=\frac{1}{\omega} \sin^{-1}(\frac{x}{A}) ##, so that ## f(x) \Delta x=\Delta t/(T/2)=(\frac{1}{\pi A}) \frac{1}{\sqrt{1-(\frac{x}{A})^2 } } \Delta x ##. The function ## f(x) ## has the necessary properties. (Note: There's actually a +/- sign on the derivative, but it works to just keep the + sign. We are considering ## -T/4<t<T/4 ## with ## -A<x<A ## which is a half cycle of the pendulum). ## \\ ## For the problem at hand ## A=5 ## and the half width of the pond is ##2 ## , so to get the probability ##P=\int\limits_{-2}^{2} f(x) \, dx ## that it lands in the pond. Meanwhile ## T=2 \pi \sqrt{L/g} ## where ## g=9.8 \, m/sec^2 ##, and ## \omega=2 \pi /T ##. But this is extra information.
 
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  • #5
Note: I made a correction to the above: ## \omega T=2 \pi ##, thereby the ##1/(\pi A) ## term in ## f(x) ##. ## \\ ## The integral ## P=(\frac{1}{ 5 \pi }) \int\limits_{-2}^{2} \frac{1}{\sqrt{1-(x/5)^2}} \, dx ## can be readily performed, and the result is ##P= (\frac{2}{\pi}) \sin^{-1}(2/5) \approx .26 ##. ## \\ ## Had the half width of the pond been equal to 5, then ## P=(\frac{2}{\pi}) \sin^{-1}(5/5)=(\frac{2}{\pi})(\frac{\pi}{2})=1 ##.
 
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1. What is a probability density function (PDF)?

A probability density function is a mathematical function that describes the likelihood of a continuous random variable taking on a specific range of values. It is used to visualize the probability distribution of a variable and can be used to calculate the probability of a variable falling within a certain range.

2. How is a PDF different from a probability mass function (PMF)?

A probability mass function is used for discrete random variables, while a probability density function is used for continuous random variables. A PMF gives the probability of specific values occurring, while a PDF gives the probability of a variable falling within a range of values. In other words, a PMF gives a probability for each possible outcome, while a PDF gives a probability for a range of outcomes.

3. How do you interpret a PDF graph?

A PDF graph shows the probability distribution of a variable, meaning it shows the likelihood of different values occurring. The higher the curve on the graph, the more likely that value is to occur. The area under the curve represents the total probability, and the area between two points on the curve represents the probability of the variable falling within that range.

4. How is a PDF used in statistics and data analysis?

A PDF is used to analyze and understand the probability distribution of a variable in a dataset. It can be used to calculate the probability of certain outcomes, compare different datasets, and make predictions about future outcomes. It is also used to determine the most likely values and identify any outliers or unusual patterns in the data.

5. Can a PDF be used for any type of data?

A PDF is typically used for continuous data, such as height, weight, or time. However, it can also be used for discrete data if the number of possible values is very large, making it difficult to create a probability mass function. In general, a PDF is most useful for data that can be measured on a continuous scale.

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