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 ...

Selecting a random sample from a set is simple. But what about selecting a fair random sample from a set of unknown or indeterminate size? That’s where reservoir sampling comes in, and [Sam Rose] has ...

Sampling is a tool researchers use for marketing, sociology or empirical study. In order for sampling to be productive, the data analysis must not be tainted. There are techniques for creating a ...

Stratified mean-per-unit sampling is a key tool used by auditors. The popularity of this statistical procedure arises from its unique ability to produce trustworthy ...

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 ...

The problem of estimating the variance of the ratio estimator in sampling with probability proportional to aggregate size is investigated. The form of nonnegative unbiased variance estimators is found ...