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View allChapter 13: Statistics — Class 11 Mathematics
Chapter 13: Statistics
Summary
Measures of central tendency (mean, median, mode) tell where data are centred but not how spread out they are. This chapter studies measures of dispersion: range, mean deviation, variance and standard deviation. The range is simply maximum minus minimum. The mean deviation about a central value \(a\) (mean or median) is the average of the absolute deviations: for ungrouped data \(\text{M.D.}(\bar x)=\dfrac{1}{n}\sum|x_i-\bar x|\), with frequency-weighted versions for grouped data. Because absolute values are awkward to manipulate, variance squares the deviations: \(\sigma^2=\dfrac{1}{n}\sum (x_i-\bar x)^2\), and the standard deviation \(\sigma=\sqrt{\sigma^2}\) restores the original units. For a frequency distribution, \(\sigma=\dfrac{1}{N}\sqrt{N\sum f_i x_i^2-\left(\sum f_i x_i\right)^2}\), and a step-deviation (shortcut) method simplifies the arithmetic. Adding a constant to every observation leaves the variance unchanged, while multiplying by \(k\) multiplies the variance by \(k^2\). These measures let us compare the consistency of two data sets with the same mean.
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