Graduate course in probability

By:

Nicolaescu, Liviu I

Material type: Text

TextPublication details: World Scientific 2023 SingaporeDescription: 541pISBN:

9781944660680

Subject(s):

Probabilities

DDC classification:

519.2 NIC

Summary: This book is an introduction to probability, aimed at aspiring probabilists and serving as a textbook for a basic graduate course. It emphasizes measure theory and integration aspects with special probabilistic uses. The book covers topics relevant to an aspiring probabilist's culture and is guided by the author's belief that probability is a theory driven by examples. The book includes an eclectic collection of examples from classical to modern, mainstream to exotic. Nearly 200 exercises are included to enhance comprehension and expand the reader's horizons. The author discovered the power of simulations while teaching probability at both undergraduate and graduate levels, inviting readers to familiarize themselves with the programming language R. The book is written by a probability outsider, bringing a bit of freshness and naiveties.

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Holdings
Item type	Current library	Collection	Call number	Status	Date due	Barcode	Item holds
Book	Jammu General Stacks	Non-fiction	519.2 NIC (Browse shelf(Opens below))	Available		IIMJ-8885

Total holds: 0

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Previous	519.2 HUN Effect : an introduction to research design and causality	519.2 KOR Stochastic processes with R : an introduction	519.2 MOS Introduction to probability theory : a first course on the measure-theoretic approach	519.2 NIC Graduate course in probability	519.2 TIJ Basic probability : what every math student should know	519.3 CAR Game theory and behavior	519.3 DIX Games of strategy /	Next

1. Foundations 2. Limit theorems 3. Martingales 4. Markov chains 5. Elements of Ergodic Theory

This book is an introduction to probability, aimed at aspiring probabilists and serving as a textbook for a basic graduate course. It emphasizes measure theory and integration aspects with special probabilistic uses. The book covers topics relevant to an aspiring probabilist's culture and is guided by the author's belief that probability is a theory driven by examples. The book includes an eclectic collection of examples from classical to modern, mainstream to exotic. Nearly 200 exercises are included to enhance comprehension and expand the reader's horizons. The author discovered the power of simulations while teaching probability at both undergraduate and graduate levels, inviting readers to familiarize themselves with the programming language R. The book is written by a probability outsider, bringing a bit of freshness and naiveties.

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