Mean/Variance of Uniform Probability Distribution

In summary, to find the mean and variance of a uniform probability distribution with f(x) = 1/x for x = 1,2,3,...,n, we can use the formulas for mean and variance given in the hint. The mean is the sum of products of x and its probability of occurring, while the variance is the sum of (x - mean)^2 multiplied by its probability of occurring. Since the probabilities in this case are all equal to 1/n, the formulas for mean and variance can be simplified by dividing the sums by n.
  • #1
JeffNYC
26
0
Find the mean and variance of the uniform probability distribution:

f(x) = 1/x for x = 1,2,3,...,n

Hint: The sum of the first positive n integers is n(n + 1)/2, and the sum of their squares is n(n + 1)(2n + 1)/6

I know mu/mean will be the sum of products of x and its probability of occurring over all x (through n in this case). I just don't know how to incorporate the formulas given in the hint into the general formulas for mean and variance:

[tex]\Sigma[/tex]xf(x) is the mean


[tex]\Sigma[/tex] (x - [tex]\mu[/tex])2 f(x) is the variance.

Thank you for your help, (I don't know why mu is elevated.)

Jeff
 
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  • #2
Since you have the first 2 moments, the variance formula can be simplified.
variance=second moment - square of first moment. (This comes directly from the definition).

Notes: f(x)=1/n, not 1/x. To get the moments, your sums must be divided by n.
 
  • #3
Mathman - can you show me how to calculate the first and second moments of the probability distribution?
 
  • #4
The moments in your case are simply the sums divided by n. In general if the probabilites are unequal, then you sum the numbers (first moment) or squares (second moment) multiplied by the probabilities.
 

What is the mean of a uniform probability distribution?

The mean, or average, of a uniform probability distribution is equal to the midpoint of the distribution. This means that all values in the distribution are equally likely to occur, and the sum of all values divided by the number of values will give the mean.

How is the mean of a uniform probability distribution calculated?

The mean of a uniform probability distribution is calculated by taking the sum of all values in the distribution and dividing it by the number of values. Mathematically, the mean can be represented as (a+b)/2, where a and b are the minimum and maximum values in the distribution, respectively.

What is the variance of a uniform probability distribution?

The variance of a uniform probability distribution measures the spread or variability of the distribution. It tells us how far the values in the distribution are from the mean. In a uniform probability distribution, the variance is calculated as (b-a)^2/12, where a and b are the minimum and maximum values in the distribution, respectively.

How is the variance of a uniform probability distribution calculated?

The variance of a uniform probability distribution is calculated by taking the difference between the maximum and minimum values in the distribution, squaring it, and dividing it by 12. This formula is derived from the general formula for calculating variance, and takes into account the fact that all values in a uniform distribution have equal probability.

What is the relationship between mean and variance in a uniform probability distribution?

In a uniform probability distribution, the mean and variance are directly related. This means that as the mean increases, so does the variance, and vice versa. This relationship can be seen in the formula for calculating variance, where the difference between the maximum and minimum values is squared. This means that a larger range of values will result in a larger variance.

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