Sum of Squared Deviations from Mean/Corollary 1

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Theorem

Let $S = \set {x_1, x_2, \ldots, x_n}$ be a set of real numbers.

Let $\overline x$ denote the arithmetic mean of $S$.


Then:

$\ds \sum_{i \mathop = 1}^n \paren {x_i - \overline x}^2 = \sum_{i \mathop = 1}^n x_i^2 - n \overline x^2$


Proof

\(\ds \sum_{i \mathop = 1}^n \paren {x_i - \overline x}^2\) \(=\) \(\ds \sum_{i \mathop = 1}^n \paren {x_i^2 - \overline x^2}\) Sum of Squared Deviations from Mean
\(\ds \) \(=\) \(\ds \sum_{i \mathop = 1}^n x_i^2 - \sum_{i \mathop = 1}^n \overline x^2\) Summation is Linear
\(\ds \) \(=\) \(\ds \sum_{i \mathop = 1}^n x_i^2 - n \overline x^2\) Sum of Identical Terms

$\blacksquare$