Discover how sample size neglect impacts statistical conclusions and learn to avoid this cognitive bias studied by renowned experts like Tversky and Kahneman.

Systematic sampling is straightforward and low risk, offering better control. However, it may introduce sampling errors and ...

Power analyses and sample size calculations are important parts of many research projects. Often, before data are even collected, it is necessary to calculate and justify the required sample size for ...

Sampling is a technique in which samples are drawn at random (without any favor or bias). For this, suitable measures or procedures may be laid down and adopted according to the nature and ...

Back in the day, we learned in statistics that you need a sample size of at least 2% of the size of population to make statistically significant conclusions about the behavior of the population. In ...

In the first part of this piece I pointed out why it can be difficult to validate TAR using control set metrics. When the overall proportion of responsive documents is very low, it becomes ...