Probability Density Function

In summary, the problem involves finding the number of fragments within 10 kilometers of a volcanic eruption's center, given a density function. The correct method for solving this involves using a double integral in polar coordinates, with the result being 2*pi times the integral of the density function from 0 to 10.
  • #1
radeksrat
1
0
Not really a homework question, but a problem I don't get nonetheless.



The density of fragments lying x kilometers from the center of a volcanic eruption is given by:

D(r) = 1/[sqrt(x) +2] fragments per square kilometer. To 3 decimal places, how many fragments will be found within 10 kilometers of the eruption's center?



I thought I was supposed to integrate the function from 0 to 100*pi, and in doing so I got 26.294, (I got 2[sqrt(x) - 2*ln(sqrt(x)+2)] when i integrated the function) but the answer was given to me as 70.424. The answer could very well be wrong, but I don't know that it is. What, if anything, am I doing wrong here?
 
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  • #2
in cylindrical coordinates the integral of the density gives the distribution.
In this case the problem requires integrating over an area thus we have a double integral. In polar form J = int(int(f(r,theta)*r*dr)*dtheta) With the appropriate limits. Then J = int(int(1/(sqrt(x)+2),x) from 0 to 10,theta from 0 to 2pi) The result is simpler because theta does not appear inside the integral. The result is 2*pi*int(1/(sqrt(x)+2),x) from 0 to 10. That should be your answer
 
  • #3
I'm not sure what you mean by ,x) abercrombie, but to be clear, the integral is
[tex]\int_{0}^{2 \pi}\int_{0}^{10} \frac{x}{\sqrt{x}+2} dx d\theta[/tex]
because of the jacobian x.
 

1. What is a Probability Density Function (PDF)?

A Probability Density Function (PDF) is a mathematical function that describes the likelihood of a continuous random variable taking on a certain value or range of values. It is used to model and analyze the probability distribution of a continuous variable, such as height or weight.

2. How is a PDF different from a Probability Mass Function (PMF)?

A Probability Mass Function (PMF) is used to describe the probability distribution of a discrete random variable, where the possible values are countable. A PDF, on the other hand, is used for continuous random variables where the possible values are infinite and uncountable.

3. What is the area under a PDF curve?

The area under a PDF curve represents the probability of a continuous random variable taking on a certain value or falling within a certain range of values. The total area under the curve is equal to 1, as the probability of any possible outcome must add up to 1.

4. How is a PDF used in statistical analysis?

A PDF is used in statistical analysis to determine the probability of a certain outcome or range of outcomes for a continuous random variable. It can also be used to calculate the mean, median, and standard deviation of the variable.

5. Can a PDF be used to predict the exact outcome of a continuous random variable?

No, a PDF cannot be used to predict the exact outcome of a continuous random variable. It only provides information on the likelihood of different outcomes or ranges of outcomes. The actual outcome of a continuous variable will still be subject to chance and cannot be determined with certainty.

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