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2. Standard error - Wikipedia

   en.wikipedia.org/wiki/Standard_error

   With n = 2, the underestimate is about 25%, but ... value to calculate ... to approximate the population standard deviation as the sample size increases. ...

3. Standard deviation - Wikipedia

   en.wikipedia.org/wiki/Standard_deviation

   When only a sample of data from a population is available, the term standard deviation of the sample or sample standard deviation can refer to either the above-mentioned quantity as applied to those data, or to a modified quantity that is an unbiased estimate of the population standard deviation (the standard deviation of the entire population).

4. Central limit theorem - Wikipedia

   en.wikipedia.org/wiki/Central_limit_theorem

   The scaled sum of a sequence of i.i.d. random variables with finite positive variance converges in distribution to the normal distribution. In probability theory, the central limit theorem ( CLT) states that, under appropriate conditions, the distribution of a normalized version of the sample mean converges to a standard normal distribution.

5. Algorithms for calculating variance - Wikipedia

   en.wikipedia.org/wiki/Algorithms_for_calculating...

   Sum ← Sum + x. SumSq ← SumSq + x × x. Var = (SumSq − (Sum × Sum) / n) / (n − 1) This algorithm can easily be adapted to compute the variance of a finite population: simply divide by n instead of n − 1 on the last line. Because SumSq and (Sum×Sum)/n can be very similar numbers, cancellation can lead to the precision of the result to ...

6. Standard normal table - Wikipedia

   en.wikipedia.org/wiki/Standard_normal_table

   Standard normal table. In statistics, a standard normal table, also called the unit normal table or Z table, [ 1] is a mathematical table for the values of Φ, the cumulative distribution function of the normal distribution. It is used to find the probability that a statistic is observed below, above, or between values on the standard normal ...

7. Circular error probable - Wikipedia

   en.wikipedia.org/wiki/Circular_error_probable

   CEP is not a good measure of accuracy when this distribution behavior is not met. Munitions may also have larger standard deviation of range errors than the standard deviation of azimuth (deflection) errors, resulting in an elliptical confidence region. Munition samples may not be exactly on target, that is, the mean vector will not be (0,0).