Core Principles of Probability and Statistical Inference
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Fundamental Theorems in Probability
The Law of Large Numbers
The Law of Large Numbers is a theorem in probability that describes the average behavior of a succession of random variables as the total number of variables increases. The theorem provides sufficient hypotheses to affirm that the sample average converges to the average of the expectations of the random variables involved.
Chebyshev's Theorem
Chebyshev's Theorem provides an upper bound on the probability that values fall outside a certain range from the average.
Bernoulli's Theorem
Bernoulli's Theorem is a special case of the Law of Large Numbers, which specifies that the approximate frequency of an occurrence converges to the probability p of that occurrence as the experiment is repeated.... Continue reading "Core Principles of Probability and Statistical Inference" »