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In regards to the stock market returns, what is the significance of the Law of Large Numbers?
What do confidence intervals represent?
What are the differences between z-statistics and t-statistics?
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In a statistical context, laws of large numbers imply that the average of a random sample from a large population is likely to be close to the mean of the whole population.
In probability theory, several laws of large numbers say that the average of a sequence of random variables with a common distribution converges (in the senses given below) to their common expectation, in the limit as the size of the sequence goes to infinity. Various formulations of the law of large numbers, and their associated conditions, specify convergence in different ways.
When the random variables have a finite variance, the central limit theorem extends our understanding of the convergence of their average by describing the distribution of the standardised difference between the sum of the random variables and the expectation of this sum. Regardless of the underlying distribution of the random variables, this ...
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