# Rando Mth

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**Variance** is the measure of spread
*Read as: the variance (sigma
squared) is equal to the squared mean minus the mean squared*

The **mean** is calculated via the **sum** of all the variables in an array,
`1`

continue until `n`

and execute the logic to the right of the **sum** symbol, that weird E
looking thing. So as it iters it’s adding the previous indexed logic to the current, etc. It’s
simply a for loop if you’re a programmer!

Ending this, we calculate the **squared mean** by simply squaring `x`

,
**line** above the variable means, well, the mean and the squared part tells us how the
array was summed.

The **standard deviation** is the root of variance. As we will see in the future, the standard
deviation is often used in calculations where we want to quantify how “surprising” a particular
observation is.

The reason we do a squared difference is bc when we square the distances we get a quantity that
increases whenever the data set becomes more spread out AND to make the distances non-negative,
otherwise the difference would always be `0`

, no matter how spread out the distribution is!

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