On Chebyshev's Other Inequality?
In Probability Theory, Chebyshev's Inequality (Also Called the Bienaymé–Chebyshev Inequality) Guarantees That, for a Wide Class of Probability Distributions...
In probability theory, Chebyshev's inequality (also called the Bienaymé–Chebyshev inequality) guarantees that, for a wide class of probability distributions, no more than a certain fraction of values can be more than a certain distance from the mean.
How do you do Chebyshev's inequality?
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Illustration of the Inequality
- For K = 2 we have 1 – 1/K2 = 1 - 1/4 = 3/4 = 75%. ...
- For K = 3 we have 1 – 1/K2 = 1 - 1/9 = 8/9 = 89%. ...
- For K = 4 we have 1 – 1/K2 = 1 - 1/16 = 15/16 = 93.75%.
What does Chebyshev's inequality measure?
Chebyshev's inequality, also known as Chebyshev's theorem, is a statistical tool that measures dispersion in a data population that states that no more than 1 / k2 of the distribution's values will be more than k standard deviations away from the mean.
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