Mean/Variance of Uniform Probability Distribution

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Discussion Overview

The discussion revolves around calculating the mean and variance of a uniform probability distribution defined by the function f(x) = 1/x for x = 1, 2, 3, ..., n. Participants explore the application of given formulas for the sums of integers and their squares in the context of probability distributions.

Discussion Character

  • Technical explanation
  • Mathematical reasoning
  • Homework-related

Main Points Raised

  • One participant, Jeff, seeks assistance in incorporating the provided formulas into the general formulas for mean and variance, expressing uncertainty about the notation used for the mean.
  • Another participant notes that the variance can be simplified using the relationship between the first and second moments, indicating that variance equals the second moment minus the square of the first moment.
  • A clarification is made regarding the probability function, stating that f(x) should be 1/n rather than 1/x, suggesting that the sums must be divided by n to obtain the moments correctly.
  • A request is made for a demonstration on how to calculate the first and second moments of the probability distribution.
  • It is mentioned that the moments are calculated as sums divided by n, with a distinction made for cases where probabilities are unequal.

Areas of Agreement / Disagreement

Participants express differing views on the correct formulation of the probability function and how to apply the formulas for mean and variance, indicating that the discussion remains unresolved.

Contextual Notes

There are limitations regarding the assumptions made about the probability function and the dependence on the definitions of moments in the context of uniform distributions. The discussion does not resolve the correct formulation of f(x) or the application of the hint provided.

JeffNYC
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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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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.
 
Mathman - can you show me how to calculate the first and second moments of the probability distribution?
 
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.
 

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