Variance and Standard Deviation

Variance and Standard Deviation

Secondary 4

Variance

Variance measures the spread or dispersion of a set of data points around their mean (average). For a group of discrete data, the variance (\(\sigma^2\)) is calculated as the average of the squared differences between each data point and the mean.

\[\sigma^2 = \frac{\sum(x - \bar{x})^2}{n}\]

Standard Deviation

The standard deviation is the square root of the variance. It gives a measure of the root-mean-square deviation from the mean, expressed in the same units as the data.

\[\sigma = \sqrt{\frac{\sum(x - \bar{x})^2}{n}}\]

Show in an algebraic way that, an alternative expression for standard deviation of a set of discrete data is given by \(\sigma = \sqrt{\frac{\sum x^2}{n} - \bar{x}^2}\).

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Answer:\(\sigma=\sqrt{\frac{\sum x^2}{n}-\bar{x}^2}\) (shown)

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