Find the median of the probability distribution

In summary, the conversation is about finding the value of C and setting up an integral in order to solve for M in the given function. The function has two parts, one being 0 <= x <= 3 and the other being 0 otherwise. After some discussion and graphing, it is concluded that the integral should be set up from M to 3 in order to solve for M, and that M lies in the range of <2 or >2.
  • #1
Phox
37
0

Homework Statement



f(x) = C|x-2| for 0 <= x <= 3
f(x) = 0 otherwise

Homework Equations





The Attempt at a Solution


Solved for C, found it to be (2/5).

So.. I'm confused how to set up my integral here. I tried integral(2/3(x-2)dx) from m to 3 = 1/2. That didn't yield the correct result.
 
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  • #2
Phox said:

Homework Statement



f(x) = C|x-2| for 0 <= x <= 3
f(x) = 0 otherwise

Homework Equations



The Attempt at a Solution


Solved for C, found it to be (2/5).

So.. I'm confused how to set up my integral here. I tried integral(2/3(x-2)dx) from m to 3 = 1/2. That didn't yield the correct result.
If you found C to be 2/5, then the integral should be
[itex]\displaystyle \int_{M}^{3}\frac{2}{5}|x-2|\,dx \ .[/itex]​

Set that equal to 1/2 and solve for M, although it might be easier to integrate from 0 to M.

Graph the integrand to see why.
 
Last edited:
  • #3
SammyS said:
If you found C to be 2/5, then the integral should be
[itex]\displaystyle \int_{M}^{3}\frac{2}{5}|x-2|\,dx \ .[/itex]​

Set that equal to 1/2 and solve for M, although it might be easier to integrate from 0 to m.

Graph the integrand to see why.

Yes, actually that's what I meant to say. I don't understand how I can integrate the function having the absolute value there. I understand how to do it if it were say.. integrating from 0 to 3. But since we don't know what m is I don't understand.

And neither does wolfram alpha lol
 
  • #4
Phox said:
Yes, actually that's what I meant to say. I don't understand how I can integrate the function having the absolute value there. I understand how to do it if it were say.. integrating from 0 to 3. But since we don't know what m is I don't understand.

And neither does wolfram alpha lol
Did you graph the function?

If x ≤ 2, then |x - 2| = 2 - x .

If x ≥ 2, then |x - 2| = x - 2 .
 
Last edited:
  • #5
Yes, and I understand that. What I don't understand is where m lies. Is it in the range of <2 or >2
 
  • #6
Phox said:
Yes, and I understand that. What I don't understand is where m lies. Is it in the range of <2 or >2

That is what you need to figure out. If in doubt, try it both ways to see what happens! However, careful examination of your graph should be enough.
 

1. What is the median of a probability distribution?

The median of a probability distribution is the middle value of a set of data when arranged in ascending or descending order. It divides the data into two equal parts, with 50% of the values falling below the median and 50% above.

2. How is the median calculated for a probability distribution?

The median is calculated by arranging the data in ascending or descending order and then identifying the middle value. If there is an even number of data points, the median is the average of the two middle values.

3. What is the importance of finding the median in a probability distribution?

The median is an important measure of central tendency in a probability distribution because it is less affected by extreme values or outliers compared to the mean. It provides a better representation of the "typical" value in a dataset.

4. Can the median be used to describe a skewed probability distribution?

Yes, the median can still be used to describe a skewed probability distribution. However, in cases of highly skewed distributions, the median may not accurately reflect the central tendency of the data.

5. How does the median differ from the mode and mean in a probability distribution?

The mode is the most frequently occurring value in a dataset, while the mean is the average of all the values. The median, on the other hand, is the middle value. Unlike the mean, the median is not affected by extreme values, and unlike the mode, it takes into account all the values in the dataset.

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