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In order to understand the sampling distribution you need to know that it is a central limit theorem that states: while in a given population which is represented through the finite non-zero variance σ2 and a finite mean μ there is a possibility of experiencing the sampling distribution of the mean. This approaches the normal distribution along with mean of μ and with variance of σ2/N as N represents the sample size which may increase.
Understanding the sampling distribution of mean
Myhomeworkhelp.com offers the sampling distribution of the sample mean assignment help that makes you knowledgeable about the topic. It is a distribution of sample means which is described with and .
Such parameters appear to be in relation with the other parameters of the population distribution. The only need of the central limit theorem in case of statistics is that it helps in thinking about the hypothesis testing as well as it follows the sampling theory which depends on this theorem.
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