  # Class 11 Maths Revision Notes for Statistics of Chapter 15 – Free PDF Download

Free PDF download of Class 11 Maths revision notes & short key-notes for Statistics of Chapter 15 to score high marks in exams, prepared by expert mathematics teachers from latest edition of CBSE books.

 Chapter Name Statistics Chapter Chapter 15 Class Class 11 Subject Maths Revision Notes Board CBSE TEXTBOOK MatheMatics Category REVISION NOTES

## CBSE Class 11 Maths Revision Notes for Statistics of Chapter 15

Measure of Dispersion
The dispersion is the measure of variations in the values of the variable. It measures the degree of scatteredness of the observation in a distribution around the central value.
Range
The measure of dispersion which is easiest to understand and easiest to calculate is the range.
Range is defined as the difference between two extreme observation of the distribution.
Range of distribution = Largest observation – Smallest observation.
Mean Deviation
Mean deviation for ungrouped data
For n observations x1, x2, x3,…, xn, the mean deviation about their mean is given by Mean deviation about their median M is given by Mean deviation for discrete frequency distribution
Let the given data consist of discrete observations x1, x2, x3,……., xn occurring with frequencies f1, f2, f3,……., fn respectively in case Mean deviation about their Median M is given by Mean deviation for continuous frequency distribution where xi are the mid-points of the classes, and M are respectively, the mean and median of the distribution.
Variance
Variance is the arithmetic mean of the square of the deviation about mean .
Let x1, x2, ……xn be n observations with as the mean, then the variance denoted by σ2, is given by Standard deviation
If σ2 is the variance, then σ is called the standard deviation is given by Standard deviation of a discrete frequency distribution is given by Standard deviation of a continuous frequency distribution is given by Coefficient of Variation
In order to compare two or more frequency distributions, we compare their coefficient of variations. The coefficient of variation is defined as Note: The distribution having a greater coefficient of variation has more variability around the central value, then the distribution having a smaller value of the coefficient 0f variation.