Help with understanding a solution in statistics

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The discussion centers on understanding the calculation of variance in a statistics problem involving rounding errors. The round-off errors are uniformly distributed over the interval [-0.5, 0.5], and the question seeks the probability that the rounded sum exceeds the exact sum by more than 3. The variance is derived from the definition, specifically by calculating E[x^2] for a uniform distribution, which results in the value of 1/12. Participants clarify the correct interpretation of the problem's wording, emphasizing the importance of the specified interval. This explanation aids in grasping the statistical concepts necessary for the upcoming exam.
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http://kaharris.org/teaching/425/Lectures/lec37.pdf

"Fifty numbers are rounded-off to the nearest integer and the summed.
Suppose that the individual round-off errors are uniformly distributed
over (0:5; 0:5). What is the probability that the round-off error
exceeds the exact sum by more than 3?"I don't understand how they calculate the variance where they get the 1/12

This isn't homework nor am I taking a class in statistics. I will however be taking an exam in statistics so I can credit for a class in statistics in May. Any help will be appreciated.
 
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The problem wording is rather bad and confusing. If I try to render what it should be, I get something like
Fifty numbers are rounded-off to the nearest integer and then summed.
Suppose that the individual round-off errors are uniformly distributed
over the interval [-0.5, 0.5]. What is the probability that the rounded-off sum exceeds the exact sum by more than 3?
Your question where the ##\tfrac {1} {12}## comes from, can be answered with a simple: from the definition of the variance: calculate E[x2] for a uniform distribution.
In your lecture suite: lecture 20.
 
xdrgnh said:
Suppose that the individual round-off errors are uniformly distributed
over (0:5; 0:5).
The interval should read "[-0.5, 0.5]".
 
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