Finding the median of a distribution

In summary: Y ~ N(0,1), where N(x) = 1 - x2. Therefore, the cumulative distribution of y is F(y) = P(y > 1 - x2) = P(y > 0) + P(y < 0)
  • #1
doctordiddy
54
0

Homework Statement


Suppose X has the Uniform (0,1) distribution. Find the median of the distribution of e^X correct to 2 decimals.

Homework Equations


F(X) = 0.5
F(X) = ∫f(x)

The Attempt at a Solution


I am not entirely sure what to do here, I know to find the median you need to find when F(X) = 0.5. I assumed that e^X was just the cdf f(x) = e^X which makes F(x) still e^X.

So then I used e^(X) = 0.5 which gives X = ln(0.5).

However this is not correct. I am a bit confused about the first part of the question, how X being a uniform distribution would affect it.

Any help would be appreciated

Thanks
 
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  • #2
doctordiddy said:

Homework Statement


Suppose X has the Uniform (0,1) distribution. Find the median of the distribution of e^X correct to 2 decimals.

Homework Equations


F(X) = 0.5
F(X) = ∫f(x)

The Attempt at a Solution


I am not entirely sure what to do here, I know to find the median you need to find when F(X) = 0.5. I assumed that e^X was just the cdf f(x) = e^X which makes F(x) still e^X.

So then I used e^(X) = 0.5 which gives X = ln(0.5).
If you think about it a bit, this can't be right, since X would have to be a negative number. If X ranges from 0 to 1, then e^X will range from ? to ?
doctordiddy said:
However this is not correct. I am a bit confused about the first part of the question, how X being a uniform distribution would affect it.

Any help would be appreciated

Thanks
 
  • #3
I found the answer to be e^0.5, but I am not sure exactly why. Do we find the median of the uniform distribution of X (0.5) and then plug that into e^(X)? Or do I need to find the median of the distribution between 1 and e? If it's the latter, how do we know that the median is simply e^(0.5)? Are we able to say this because X is a uniform distribution?
 
  • #4
Mark44 said:
If you think about it a bit, this can't be right, since X would have to be a negative number. If X ranges from 0 to 1, then e^X will range from ? to ?
I found the answer to be e^0.5, but I am not sure exactly why. Do we find the median of the uniform distribution of X (0.5) and then plug that into e^(X)? Or do I need to find the median of the distribution between 1 and e? If it's the latter, how do we know that the median is simply e^(0.5)? Are we able to say this because X is a uniform distribution?
 
  • #5
doctordiddy said:
I found the answer to be e^0.5, but I am not sure exactly why. Do we find the median of the uniform distribution of X (0.5) and then plug that into e^(X)? Or do I need to find the median of the distribution between 1 and e? If it's the latter, how do we know that the median is simply e^(0.5)? Are we able to say this because X is a uniform distribution?

If ##Y = e^X##, the cumulative distribution of ##Y## is ##F(y) = P(Y \leq y) = P(e^X \leq y)##. For ##X \sim U(0,1)##, what does this give you for ##F(y)##? What is the solution of ##F(y) = 1/2##? That would give you the median.
 
  • #6
Ray Vickson said:
If ##Y = e^X##, the cumulative distribution of ##Y## is ##F(y) = P(Y \leq y) = P(e^X \leq y)##. For ##X \sim U(0,1)##, what does this give you for ##F(y)##? What is the solution of ##F(y) = 1/2##? That would give you the median.

I am unsure of how to continue after
For ##X \sim U(0,1)##, what does this give you for ##F(y)##? Am I supposed to see that X = ln(y) or am I supposed to see that Y ~ U(1,e)? Or am I missing something altogether?
 
  • #7
doctordiddy said:
Am I supposed to see that X = ln(y)
Some risk of confusion in the notation. That X = ln(Y) is self evident, so I'm assuming your question is why x' = ln(y'), x' and y' representing the medians of the respective distributions.
As Ray wrote, for any x, the event Y < ex is the same event as X < x. Therefore FY(ex) = FX(x). Setting x=x' we get FY(ex') = 0.5.
doctordiddy said:
am I supposed to see that Y ~ U(1,e)
That is certainly not the case.
 

1. What is the median of a distribution?

The median of a distribution is the middle value when the data is arranged in order from smallest to largest. It divides the data into two equal parts, with half of the data falling below the median and the other half above.

2. How is the median different from the mean?

The median and the mean are both measures of central tendency, but they represent different aspects of the data. While the median represents the middle value, the mean is the average of all the values in the distribution. The median is less affected by extreme values or outliers, making it a more robust measure of central tendency.

3. How do you find the median when there is an even number of data points?

If there is an even number of data points, the median is the average of the two middle values. For example, if there are 10 data points, the median is the average of the 5th and 6th values when the data is arranged in order.

4. What is the significance of the median in a distribution?

The median is an important measure in a distribution because it represents the value that divides the data into two equal parts. It is less affected by extreme values, giving a more accurate representation of the central tendency of the data.

5. How is the median used in real-life applications?

The median is commonly used in real-life applications such as salary data to represent the middle income level, in housing prices to represent the middle market value, and in healthcare to represent the middle level of health outcomes. It is also used in statistical analyses to compare the distribution of data between different groups.

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