Class 11: Statistics

Measures of Dispersion, Mean Deviation, Variance & Standard Deviation

1. Basics of Dispersion

Dispersion measures how scattered the data is around a central value.

Range Difference between the maximum and minimum values.
$$Range = Maximum Value – Minimum Value$$

2. Mean Deviation (M.D.)

The arithmetic mean of the absolute deviations of observations from a central value (Mean or Median).

Data Type About Mean ($$\bar{x}$$) About Median ($$M$$)
Ungrouped Data $$M.D.(\bar{x}) = \frac{\sum |x_i – \bar{x}|}{n}$$ $$M.D.(M) = \frac{\sum |x_i – M|}{n}$$
Grouped Data
(Discrete & Continuous)
$$M.D.(\bar{x}) = \frac{\sum f_i |x_i – \bar{x}|}{N}$$
(Where $$N = \sum f_i$$)
$$M.D.(M) = \frac{\sum f_i |x_i – M|}{N}$$
Note for Median (Continuous Data):
$$Median = l + \frac{\frac{N}{2} – C}{f} \times h$$
Where $$l$$= lower limit of median class,$$N$$= total frequency,$$C$$= cumulative frequency of preceding class,$$f$$= frequency of median class,$$h$$ = class width.

3. Variance & Standard Deviation

Measures the average squared deviation from the mean. Standard Deviation ($$\sigma$$) is the square root of Variance ($$\sigma^2$$).

Ungrouped Data
Variance ($$\sigma^2$$) $$\sigma^2 = \frac{1}{n} \sum (x_i – \bar{x})^2$$
Standard Deviation ($$\sigma$$) $$\sigma = \sqrt{\frac{1}{n} \sum (x_i – \bar{x})^2}$$
Discrete Frequency Distribution
Variance ($$\sigma^2$$) $$\sigma^2 = \frac{1}{N} \sum f_i (x_i – \bar{x})^2$$
Alternate Formula $$\sigma^2 = \frac{1}{N^2} [N \sum f_i x_i^2 – (\sum f_i x_i)^2]$$
Continuous Frequency Distribution (Shortcut Method)
Step-Deviation Formula $$\sigma = \frac{h}{N} \sqrt{N \sum f_i y_i^2 – (\sum f_i y_i)^2}$$
Where $$y_i = \frac{x_i – A}{h}$$($$A$$ is assumed mean,$$h$$ is class width)