# Sum of Squares: from Definitional to Computational Formula

Sunday September 27, 2020

This is a very old draft, from perhaps 2014-08-17 or so. I don't really remember why I started the way I did, so I thought I'd keep it around. I dropped the idea of writing this up for a long time and just came back to it now.

In introductory statistics the Sum of Squares \( SS \), implicitly the sum of the squared deviations from the mean, is taught early on along with variance and standard deviation. Often a "definitional" and "computational" formula are introduced in rapid succession. Especially for folks who aren't terribly comfortable with math notation, this can be confusing. I will explain what's going on.

Here is how you get the Sum of Squares \( SS \).

You start with a bunch of numbers. Call them \( X_1, X_2, ..., X_N \). So you have \( N \) numbers.

You get the mean of these numbers, which we'll call \( \overline{X} \) (read as "x-bar"). First add up all the numbers. That's \( \sum\limits_{i=1}^{N} X_i \). This is sometimes written as just \( \sum X \) but for later clarity let's keep the limits. Then you divide that sum by \( N \) to get the average, also known as arithmetic mean, \( \overline{X} \). We'll use this equation later.

\[ \overline{X}=\frac{\sum\limits_{i=1}^{N} X_i}{N} \]

Now that we have the mean, we can go through all our numbers again.
For each one, we subtract the mean to get the deviation \( X_i -
\overline{X} \). Deviations may be positive or negative. We square
each one that we get, and we add these all up. This is the Sum of
Squares \( SS \). This is the *definition* of the Sum of
Squares. So it's called the Definitional Formula.

\[ SS=\sum\limits_{i=1}^{N} \left(X_i-\overline{X}\right)^2 \]

So far everything is very sensible. But then you hear about the Computational Formula for the Sum of Squares.

\[ SS=\sum\limits_{i=1}^{N} X_i^2-\frac{\left(\sum\limits_{i=1}^{N} X_i\right)^2}{N} \]

If you're like me, it isn't immediately clear that these two are equal. The computational formula doesn't even have the mean in it!