Longitudinal data analysis is an essential statistical approach for studying phenomena observed repeatedly over time, allowing researchers to explore both within-subject and between-subject variations ...

Bayesian analysis offers a robust framework for deciphering the intricate dynamics of time series data. By treating unknown parameters as random variables, this approach incorporates prior information ...

Functional data are defined as realizations of random functions (mostly smooth functions) varying over a continuum, which are usually collected on discretized grids with measurement errors. In order ...

Scientists have developed a method to identify symmetries in multi-dimensional data using Bayesian statistical techniques. Bayesian statistics has been in the spotlight in recent years due to ...

This course introduces the theoretical, philosophical, and mathematical foundations of Bayesian Statistical inference. Students will learn to apply this foundational knowledge to real-world data ...

If you've been planning to step up your data science game for the new year, the 2026 NPTEL course lineup from India's top IITs is honestly a goldmine. These courses cover the backbone of modern ...

The Annals of Applied Statistics, Vol. 14, No. 1 (March 2020), pp. 241-256 (16 pages) ABOUZAHR, C., CLELAND, J., COULLARE, F., MACFARLANE, S. B., NOTZON, F. C., SETEL ...

This book's organization : read me first! -- Introduction : models we believe in -- What is this stuff called probability? -- Bayes' rule -- Inferring a binomial proportion via exact mathematical ...

Objective To determine how distinct combinations of resistance training prescription (RTx) variables (load, sets and frequency) affect muscle strength and hypertrophy. Data sources MEDLINE, Embase, ...

Data modeling refers to the architecture that allows data analysis to use data in decision-making processes. A combined approach is needed to maximize data insights. While the terms data analysis and ...