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Important parts of statistical theory and its applications build on approximations to the most relevant distributions, and these approximations are valid when the sample size is large. This course ...

In probability theory, the central limit theorem (CLT) states that the distribution of a sample will approximate a normal distribution (i.e., a bell curve) as the sample size becomes larger ...

The purpose of this monograph is to give an axiomatic foundation for the theory of probability. The author set himself the task of putting in their ... Khinchine and the author of the limitations on ...

But previous Pew Research Center analyses have demonstrated how surveys that use nonprobability sampling may have errors twice as large, on average, as those that use probability sampling. The second ...

Abstract: Sharp, nonasymptotic bounds are derived for the best achievable error probability in binary hypothesis testing between two probability distributions with ...

This book provides a systematic, self-sufficient and yet short presentation of the mainstream topics on introductory Probability Theory with some selected topics from Mathematical Statistics. It is ...

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