Sampling distribution

In sampling analysis, the researcher is often concerned with sampling distribution. If a few numbers of samples are taken and for all samples of different statistical measures are computed like mean, standard deviation, we observe that each sample gives its own value for the statistic under consideration.

These values of a specific statistic like mean, with their relative frequencies would constitute the sampling distribution of the specific statistic like mean.

Similarly, the researcher can have sampling distribution of mean, sampling distribution of any statistical measure or the sampling distribution of standard deviation.

In a sampling distribution, each item to be noted here is a particular statistic of a sample. The sampling distribution gets close to the normal distribution provided the sample size is large. The importance of sampling distribution comes from the fact that the mean of a sampling distribution is similar to the mean of the entire universe. Thus, the mean of the sampling distribution could be taken as the mean of the universe.

One thought on “Sampling distribution

  1. Using mean while doing the statistical analysis helps a lot in making the entire process easy and also there are less chances of any mistakes or deviations in the results. It also saves a lot of time and it is one of the major reasons people prefer to opt for this method.

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