Markov and Chebyshev inequalities
(30 minutes to learn)
Markov's inequality and Chebyshev's inequality are tools for bounding the probability of a random variable taking on extreme values. While the bounds are weak, they apply under very general conditions. One use of Chebyshev's inequality is to prove the weak law of large numbers.
This concept has the prerequisites:
Core resources (read/watch one of the following)
→ A First Course in Probability
An introductory probability textbook.
Location: Section 8.2, "Chebyshev's inequality and the weak law of large numbers," from pages 430 to 433
→ Probability and Statistics
An introductory textbook on probability theory and statistics.
Location: Section 4.8, "The sample mean," from pages 229 to 231
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