Standard deviation is the measure of dispersion of statistical data. Dispersion computes the deviation of data from its mean or average position. The degree of dispersion is calculated by the procedure of measuring the variation of data points.

**Calculating Standard Deviation**

The formula for standard deviation makes use of three variables. The first variable is the value of each point within a data set, with a sum-number indicating each additional variable (x, x1, x2, x3, etc). The mean is applied to the values of the variable M and the number of data that is assigned to the variable n. Variance is the average of the values of squared differences from the arithmetic mean.

To calculate the mean value, the values of the data elements have to be added together and the total is divided by the number of data entities that were involved.

Standard deviation, denoted by the symbol **σ,** describes the square root of the mean of the squares of all the values of a series derived from the arithmetic mean which is also called as the root mean square deviation. 0 is the smallest value of standard deviation since it cannot be negative. When the elements in a series are more isolated from the mean, then the standard deviation is also large.

The statistical tool of standard deviation are the measures of dispersion that computes the erraticism of the dispersion among the data. For instance, mean, median and mode are the measures of central tendency. Therefore, these are considered to be the central first order averages. The measures of dispersion that are mentioned directly over are averages of deviations that result from the average values, therefore these are called as second order averages.

**Standard Deviation Formula**

**\(\sqrt{\frac{\sum \left ( x-\bar{x} \right )}{N}}\)**

**Where,**

**\(\sigma\) is the standard deviation**

**x Indicates each value of the population**

**\(\bar{x}\) shows the mean of all values**

**N is the total number of values**

The main purpose of applying standard deviation is to get a measure of the standard distance from the mean.

**Solved Example:**

Let’s say you want to calculate the standard deviation for the number of gold coins on a ship run by pirates.

There are total 100 pirates on the ship. Statistically, it means that the population is 100. We use the standard deviation equation for the entire population if we know a number of gold coins every pirate has.

Statistically, let’s consider a sample of 5 and here you can use the standard deviation equation for this sample population.

This means we have a sample size of 5 and in this case, we use the standard deviation equation for the sample of a population.

Consider the number of gold coins 5 pirates have; 4, 2, 5, 8, 6.

**Mean:**

**\(\bar{x} = \frac{\sum x}{N}\)**

=\(\frac{x_1+x_2+x_3+x_4…..+x_N}{N}\)

= (4 + 2 + 5 + 6 + 8) / 5

= 5

**\(x_n -\bar{x}\) for every value of the sample:**

\(x_1 -\bar{x}\) = 4 – 5 = -1

\(x_2 -\bar{x}\) = 2 – 5 = -3

\(x_3 -\bar{x}\) = 5 – 5 = 0

\(x_4 -\bar{x}\) = 8 – 5 = 3

\(x_5 -\bar{x}\) = 6 – 5 = 1

**\(\sum \left ( x-\bar{x} \right )\)**

= (\(x_1 -\bar{x}\))2 + (\(x_2 -\bar{x}\))2 + … +(\(x_N -\bar{x}\))2

= \((-1)^2 + (-3)^2 + 0^2 + 3^2 + 1^2\)

= 20

**Standard deviation: **\(S = \sqrt{\frac{\sum x-\bar{x}}{N – 1}}\)

= \(\sqrt{\frac{20}{5-1}}\)

= 2.24

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