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

Eeny, meeny, miny, mo, catch a tiger by the toe – so the rhyme goes. But even children know that counting-out rhymes like this are no help at making a truly random choice. Perhaps you remember when ...

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 ...

Mailing human papillomavirus (HPV) self-sampling kits to people due for cervical cancer screening was more cost effective than usual care, which included clinician electronic medical record alerts and ...

Sankhyā: The Indian Journal of Statistics, Series B (2008-), Vol. 78, No. 1 (May 2016), pp. 66-77 (12 pages) We consider the problem of unbiased estimation of a finite population mean (or proportion) ...

- In the overall modified intention-to-treat (mITT) population, improvements across all efficacy and secondary endpoints, including 24% reduction in knee pain and 26% improvement in knee function, ...

In statistics and machine learning, logistic regression is a widely-used supervised learning technique primarily employed for binary classification tasks. When the number of observations greatly ...

Importance: The United States (US) Medicare claims files are valuable sources of national healthcare utilization data with over 45 million beneficiaries each year. Due to their massive sizes and costs ...

In the real world, probability is a tough thing to characterize. If I roll a die, what does it mean to say that it has a one-sixth chance of coming up 5? We say that the outcome is random because we ...

Abstract: In this paper, the paradigm of the traditional iterative decoding schemes for the uplink large-scale MIMO detection is extended by sampling in an Markov chain Monte Carlo (MCMC) way.