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

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

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 ...

Implementation of the Time-to-Event Continuous Reassessment Method Design in a Phase I Platform Trial Testing Novel Radiotherapy-Drug Combinations—CONCORDE BayeSize applies the concept of effect size ...

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 ...

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 ...