Linganisha mbinu

	Mtandao wa Bayesian	Mofumo wa Rasch
Nyanja	Mbinu za Bayes	Saikometriki
Familia	Bayesian methods	Latent structure
Mwaka wa asili	1988	1960
Mwanzilishi	Judea Pearl	Georg Rasch
Aina	Probabilistic graphical model	Item Response Theory / Latent trait model
Chanzo asilia	Pearl, J. (1988). Probabilistic Reasoning in Intelligent Systems: Networks of Plausible Inference. Morgan Kaufmann. ISBN: 978-1558604797	Rasch, G. (1960). Probabilistic Models for Some Intelligence and Attainment Tests. Danish Institute for Educational Research, Copenhagen.
Majina mbadala	Bayes network, belief network, probabilistic graphical model, directed graphical model	1PL IRT, one-parameter logistic model, Rasch Modeli — 1PL IRT, 1PL model
Zinazohusiana	4	6
Muhtasari	A Bayesian network is a probabilistic graphical model, introduced by Judea Pearl in 1988, that encodes a set of variables and their conditional dependencies as a directed acyclic graph (DAG). Each node represents a variable; each directed edge encodes a direct probabilistic influence. By combining Bayes' rule with the graph's conditional independence structure, the model supports reasoning under uncertainty — computing the probability of any variable given observed evidence about others.	The Rasch model, introduced by Georg Rasch in 1960, is the simplest member of the Item Response Theory (IRT) family. It assigns a single difficulty parameter to each test item and places both item difficulties and person abilities on the same logit scale, enabling direct, sample-independent comparison of items and persons.