Predicting cryptocurrency prices is challenging because markets are volatile and events like regulatory changes or ETF ...

Learn how acceptance sampling improves quality control by evaluating random samples. Discover its methods, benefits, and historical significance in manufacturing.

One can argue that the underlying methodology is flawed to the point that the results cannot reasonably claim to represent ...

Background Primary healthcare is crucial for universal health coverage in low- and middle-income countries. While research on ...

From machine learning to voting, the workings of the world demand randomisation, but true sources of randomness are ...

Many healthcare providers feel that UPIC audits often fall short, with flawed sampling and extrapolation techniques that dramatically exaggerate overpayment findings, exposing providers to undue ...

Forbes contributors publish independent expert analyses and insights. Dr. Lance B. Eliot is a world-renowned AI scientist and consultant. In today’s column, I examine a newly revealed technique in ...

Background: In this paper, the basic elements related to the selection of participants for a health research are discussed. Sample representativeness, sample frame, types of sampling, as well as the ...

A discrete random variable is a type of random variable that can take on a countable set of distinct values. Common examples include the number of children in a family, the outcome of rolling a die, ...

Abstract: We proved that the phaseless sampling (PLS) in the linear-phase modulated shift-invariant space (SIS) V (eiα·φ), α = 0, is impossible even though the real-valued function φ enjoys the full ...

Abstract: This paper proposes a new perspective on the relationship between the sampling and aliasing. Unlike the uniform sampling case, where the aliases are simply periodic replicas of the original ...