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If we sampling thousand times, will obtain an distribution higher and narrow, and it is a Normal distribution.

Mean of sampling distribution is the true mean of the population. Its standard deviation (standard error) is the standard deviation in the population divided by squared root of the sample size. SE = σ/√n

We should remember that the standard error of the mean of the sample is estimate standard deviation of sampling distribution.

In real life, we only obtain a sample. Using the mean of the sample en la lugar de la media de la población and the estándar deviation (s) of the sample en lugar of σ, we can infer how is the sampling distribution. Because the distribution is Normal, 95% of the means of samples are between 1.96 standard error. Then, 95% of the means of samples are in the range: μ±1.96 (σ/√n)