Könyv Probability, Statistics and Stochastic Processes 2e Peter Olofsson

Probability, Statistics and Stochastic Processes 2e

Nyelv: Angol
Kötés: Kemény kötésű
Elérhetőség: Beszállítói készleten
Küldés 9-15 napon belül
52 046 Ft
Praise for the First Edition "...an excellent textbook ...well organized and neatly written." --Mat...

Információk a könyvről

Nyelv
Angol
Kötés
Könyv - Kemény kötésű
Kiadva
2012
oldal
572
EAN
9780470889749
ISBN
0470889748
Enbook ID
04886677
Súly
928
Méretek
163 x 245 x 33

Teljes leírás

Praise for the First Edition "...an excellent textbook ...well organized and neatly written." --Mathematical Reviews "...amazingly interesting ..." --Technometrics Thoroughly updated to showcase the interrelationships between probability, statistics, and stochastic processes, Probability, Statistics, and Stochastic Processes, Second Edition prepares readers to collect, analyze, and characterize data in their chosen fields. Beginning with three chapters that develop probability theory and introduce the axioms of probability, random variables, and joint distributions, the book goes on to present limit theorems and simulation. The authors combine a rigorous, calculus-based development of theory with an intuitive approach that appeals to readers' sense of reason and logic. Including more than 400 examples that help illustrate concepts and theory, the Second Edition features new material on statistical inference and a wealth of newly added topics, including: * Consistency of point estimators * Large sample theory * Bootstrap simulation * Multiple hypothesis testing * Fisher's exact test and Kolmogorov-Smirnov test * Martingales, renewal processes, and Brownian motion * One-way analysis of variance and the general linear model Extensively class-tested to ensure an accessible presentation, Probability, Statistics, and Stochastic Processes, Second Edition is an excellent book for courses on probability and statistics at the upper-undergraduate level. The book is also an ideal resource for scientists and engineers in the fields of statistics, mathematics, industrial management, and engineering.

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