## Standard Deviation

Standard Deviation

The mean, or average, of the data points is applied to the value of the variable M,

and the number of data points involved is assigned to the variable n.

To determine the mean value, the values of the data points must be added together, and

that total is then divided by the number of data points that were included.

If the data behaves in a normal curve, then 68% of the data points will fall within one standard deviation of the average, or mean data point.

Or to put it another way: Variance is derived by taking the mean of the data points, subtracting the mean from

each data point individually, squaring each of these results and then taking another mean of these squares.

Standard Deviation

The mean, or average, of the data points is applied to the value of the variable M,

and the number of data points involved is assigned to the variable n.

To determine the mean value, the values of the data points must be added together, and

that total is then divided by the number of data points that were included.

If the data behaves in a normal curve, then 68% of the data points will fall within one standard deviation of the average, or mean data point.

Or to put it another way: Variance is derived by taking the mean of the data points, subtracting the mean from

each data point individually, squaring each of these results and then taking another mean of these squares.

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