Central Limit Theorem: A sampling distribution of the mean is approximately normally distributed if the sample size is sufficiently large. This is true no matter what the population distribution is.

We have previously discussed the importance of estimating uncertainty in our measurements and incorporating it into data analysis 1. To know the extent to which we can generalize our observations, we ...

When an experiment is reproduced we almost never obtain exactly the same results. Instead, repeated measurements span a range of values because of biological variability and precision limits of ...

The central limit theorem (CLT) establishes that (under certain conditions) the properly normalized sum of independent random variables tends toward a normal distribution even if the original ...

When particles in a sample are the same size, one particle can be measured to report the result. If the sample has a narrow distribution, such as 10-25 µm, then measurement of just a few particles can ...