In order to estimate population parameters, it is important to have measures of how good the estimates are likely to be. For example, how well the sample mean is likely to represent the true population mean.

A precise measure defined to measure the degree of spread (standard deviation) in a set of sample statistics (e.g. means) calculated from multiple samples is called standard error. But it can also be estimated in the frame of a single sample, so the corresponding counterpart in the one-sample statistics would be $\frac{\sigma}{n^{\frac{1}{2}}} ,\,\,$ where $\sigma$ is the sample standard deviation and $n$ the sample size.

$1.\,$ In accordance with the properties of normal distribution, for example $68.27\,\% $ of the repeated means fall between the true mean and $\pm$ one sample standard deviation. I am wondering, why instead of the sample standard deviation it is not taken into consideration the estimated standard error, $\frac{\sigma}{n^{\frac{1}{2}}} \,\,$ ?

$2.\,$ When one talks about the standard error of the mean, is it about the sample standard deviation, $\sigma, \,\,$the degree of spread in a set of samples, or the estimated population standard deviation out of a single sample, $\frac{\sigma}{n^{\frac{1}{2}}} \,\,$ ?

$3.\,$ In the formula $$P\,\{ \bar y- t_{0.05(n-1)}s_{\bar y}\leq \mu \leq\bar y +t_{0.05(n-1)} s_{\bar y}\}\,\,,$$ where $\mu $ is the unknown polpulation mean, $\bar y$ is the sample mean, what kind of error is $s_{\bar y}$, i.e. is it the sample $\sigma$, maybe $\frac{\sigma}{n^{\frac{1}{2}}},$ or something else ?

Many thanks.


1 Answer 1


In 1, it is about $68.27\%$ of the observations that are within one standard deviation of the mean. The standard deviation of your estimate of the mean is $\frac {\sigma}{n^{\frac 12}}$. Both are fine formulas, but they are referring to different things. I don't know how you estimate the standard deviation from a single sample.

  • $\begingroup$ Thanks. The standard deviation in a set of samples according to my statistics book is estimated by $\frac {\sigma}{n^{\frac 12}},\,$ where $\sigma$ is the standard deviation of the single sample. When you are saying standard deviation of the mean, do you mean the standard deviation of a single sample or of a set of samples ? You are also saying that both formulas are referring to different things. Can you be more explicit and explain it ? $\endgroup$
    – user249018
    Commented Mar 11, 2018 at 16:53
  • $\begingroup$ The standard deviation of the mean is the standard deviation of your estimate of the mean based on $n$ samples. You take the samples and average them to estimate the mean of the distribution. Then you ask what is the standard deviation of that estimate $\endgroup$ Commented Mar 11, 2018 at 21:57

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