# Thursday, June 8

Assignment 9.4 Task + RSG. In class notes on standard deviation

Note: The formula for standard deviation involves $\dpi{300}\inline \Sigma$ (Greek, "Sigma") or "sum" notation. $\dpi{300}\inline x_i$ refers to the ith element in the data set, $\dpi{300}\inline \overline{x}$ is the mean x-value.

$\dpi{300}\inline SD = \sqrt{\dfrac{\sum_{i=1}^{N}(x_i - \overline{x})^2}{N}}$

1. Find the difference between each value and the mean

$\dpi{300}\inline (x_i - \overline{x})$

2. Square those differences

$\dpi{300}\inline (x_i - \overline{x})^2$

3. Find the sum of all of the squares

$\dpi{300}\inline \sum_{i=1}^{N}(x_i - \overline{x})^2$

4. Divide that value by N (the number of data elements in the set)

$\dpi{300}\inline \dfrac{\sum_{i=1}^{N}(x_i - \overline{x})^2}{N}$

5. The Standard Deviation is the square root of the result

$\dpi{300}\inline SD = \sqrt{\dfrac{\sum_{i=1}^{N}(x_i - \overline{x})^2}{N}}$

One way to understand the standard deviation is that it is kind of like the average distance from the mean in the data set.