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Probabilistic Systems Analysis and Applied Probability (2013)
Duración media del audio:
25 minutes
Inglés
Estados Unidos
76 episodios
desde 7 de julio de 2015
episodic
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EPISODIOS ANTERIORES 🔗
In this lecture, the professor discussed classical inference, Linear regression, and binary hypothesis testing.
In this lecture, the professor discussed classical statistics, maximum likelihood (ML) estimation, and confidence intervals.
In this lecture, the professor discussed classical inference, simple binary hypothesis testing, and composite hypotheses testing.
In this lecture, the professor discussed Bayesian statistical inference, least means squares, and linear LMS estimation.
In this lecture, the professor discussed Bayesian statistical inference and inference models.
In this lecture, the professor discussed central limit theorem, Normal approximation, 1/2 correction for binomial approximation, and De Moivre–Laplace central limit theorem.
In this lecture, the professor discussed limit theorems, Chebyshev's inequality, and convergence "in probability".
In this lecture, the professor discussed Markov Processes, probability of blocked phone calls, absorption probabilities, and calculating expected time to absorption.
In this lecture, the professor discussed Markov process, steady-state behavior, and birth-death processes.
Descargo de responsabilidad: El podcast y el arte incluidos en esta página son de John Tsitsiklis, Qing He, Jimmy Li, Jagdish Ramakrishnan, Katie Szeto, Kuang Xu, que es propiedad de su propietario y no está afiliado ni respaldado por Listen Notes, Inc.
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