释义 |
Weak Law of Large NumbersAlso known as Bernoulli's Theorem. Let , ..., be a sequence of independent and identically distributedrandom variables, each having a Mean and Standard Deviation . Define a new variable
 | (1) |
Then, as , the sample mean equals the population Mean of each variable.
 | (2) |
Therefore, by the Chebyshev Inequality, for all ,
 | (4) |
As , it then follows that
 | (5) |
for arbitrarily small; i.e., as , the sample Mean is the same as the population Mean.
Stated another way, if an event occurs times in Trials and if is the probability of successin a single Trial, then the probability that for an arbitrary Positive quantityapproaches 1 as . See also Law of Truly Large Numbers, Strong Law of Large Numbers
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