# Chebyshev’s Inequality

Chebyshev’s Inequality is used to describe the percentage of values in a distribution within an interval centered at the mean.

It states that for a distribution, the percentage of observations that lie within k standard deviations is atleast 1 – 1/k2

This is illustrated below:

**Example**

The following table shows the minimum number of observations that lie within a certain number of standard deviations of the mean.

Standard Deviations | % of observations |

1.5 | 56% |

2 | 75% |

3 | 89% |

4 | 94% |

An important feature of Chebyshev’s Inequality is that it works with any kind of distribution.

LESSONS

- Descriptive Vs. Inferential Statistics
- Types of Measurement Scales
- Parameter, Sample Statistic, and Frequency Distribution
- Relative Frequencies and Cumulative Relative Frequencies
- Properties of a Data Set (Histogram / Frequency Polygon)
- Measures of Central Tendency
- Calculating Arithmetic Mean
- Calculating Weighted Average Mean
- Calculating Geometric Mean
- Calculating Harmonic Mean
- Calculating Median and Mode of a Data Set
- Quartiles, Quintiles, Deciles, and Percentiles
- Range and Mean Absolute Deviation
- Variance and Standard Deviation
- Chebyshev’s Inequality
- Coefficient of Variation
- Sharpe Ratio
- Skewness and Kurtosis
- Relative Locations of Mean, Median and Mode

# Black Friday Deal: 51% OFF

Get our

Get it now for just $19**R Programming - Data Science for Finance Bundle**for just $19 $39. Only for this week!R Programming - Data Science for Finance Bundle

$39$19 - Black Friday Sale