Prove the sample variance formula.

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The discussion focuses on proving the sample variance formula, S² = (Σx_j² - (1/n)(Σx_j)²) / (n-1). Participants are attempting to manipulate summations and constants, particularly the sample mean, to derive the formula. Key hints emphasize that the sample mean (x̄) can be factored out of summations and that the sum of the sample values equals n times the sample mean. The conversation includes attempts to rearrange terms and clarify the relationship between the sums involved. Ultimately, the goal is to simplify the expression to reach the desired formula for sample variance.
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Homework Statement


Prove that the sample variance of a sample is given by
S2 = \frac{\sum^{n}_{j=1}x_j^2 - \frac{1}{n} (\sum^{n}_{j=1}x_j)^2}{n-1}

Homework Equations



N/A

The Attempt at a Solution



For my purposes it is sufficient to show that:

\sum^{n}_{j=1}(x_j -x_j^2) = \sum^{n}_{j=1}x_j^2 - \frac{1}{n}\left(\sum^{n}_{j=1}x_j\right)^2



I got as far as this:

= \sum^{n}_{j=1}x_j^2 - \sum^{n}_{j=1}2\bar{x}x_j + \sum^{n}_{j=1}\bar{x}^2

I need help getting from there to here:

= \sum^{n}_{j=1}x_j^2 - \frac{1}{n}\left(\sum^{n}_{j=1}x_j\right)^2

Thanks in advance and I apologize for any coding error.
 
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Hint: remember that \overline x is a constant and can be removed from summations.
 
statdad said:
Hint: remember that \overline x is a constant and can be removed from summations.

So if I put the \overline x's in front

= \sum^{n}_{j=1}x_j^2 - 2\bar{x}\sum^{n}_{j=1}x_j + \bar{x}^2\sum^{n}_{j=1}

and rearrange it I get

= \sum^{n}_{j=1}x_j^2 +\bar{x}^2\sum^{n}_{j=1} - 2\bar{x}\sum^{n}_{j=1}x_j

My instincts tell me to factor out the \overline x but I don't see how that could help.
 
The_Iceflash said:
So if I put the \overline x's in front

= \sum^{n}_{j=1}x_j^2 - 2\bar{x}\sum^{n}_{j=1}x_j + \bar{x}^2\sum^{n}_{j=1}

and rearrange it I get

= \sum^{n}_{j=1}x_j^2 +\bar{x}^2\sum^{n}_{j=1} - 2\bar{x}\sum^{n}_{j=1}x_j

My instincts tell me to factor out the \overline x but I don't see how that could help.

Hint:

<br /> \sum_{i=1}^n \overline x_i = \overline x_i \sum_{i=1}^N 1<br />

(you forgot to include the 1: what does the above sum equal?

Hint:

<br /> \overline x = \frac 1 n \sum_{i=1}^n x_i<br />

so what must

<br /> \sum_{i=1}^n x_i<br />

equal?
 
statdad said:
Hint:

<br /> \sum_{i=1}^n \overline x_i = \overline x_i \sum_{i=1}^N 1<br />

(you forgot to include the 1: what does the above sum equal?

Hint:

<br /> \overline x = \frac 1 n \sum_{i=1}^n x_i<br />

so what must

<br /> \sum_{i=1}^n x_i<br />

equal?

So, \sum_{i=1}^n x_i must be equal to n\overline x correct?

The sum from the first sum is n, correct?
 
Question: A clock's minute hand has length 4 and its hour hand has length 3. What is the distance between the tips at the moment when it is increasing most rapidly?(Putnam Exam Question) Answer: Making assumption that both the hands moves at constant angular velocities, the answer is ## \sqrt{7} .## But don't you think this assumption is somewhat doubtful and wrong?

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