Understanding Probability and Statistics
Author: Ruma Falk
Publisher: A K Peters/CRC Press
Published: 1993-04-15
Total Pages: 264
ISBN-13:
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Probability and Statistics
Author: Michael J. Evans
Publisher: Macmillan
Published: 2004
Total Pages: 704
ISBN-13: 9780716747420
DOWNLOAD EBOOK →Unlike traditional introductory math/stat textbooks, Probability and Statistics: The Science of Uncertainty brings a modern flavor based on incorporating the computer to the course and an integrated approach to inference. From the start the book integrates simulations into its theoretical coverage, and emphasizes the use of computer-powered computation throughout.* Math and science majors with just one year of calculus can use this text and experience a refreshing blend of applications and theory that goes beyond merely mastering the technicalities. They'll get a thorough grounding in probability theory, and go beyond that to the theory of statistical inference and its applications. An integrated approach to inference is presented that includes the frequency approach as well as Bayesian methodology. Bayesian inference is developed as a logical extension of likelihood methods. A separate chapter is devoted to the important topic of model checking and this is applied in the context of the standard applied statistical techniques. Examples of data analyses using real-world data are presented throughout the text. A final chapter introduces a number of the most important stochastic process models using elementary methods. *Note: An appendix in the book contains Minitab code for more involved computations. The code can be used by students as templates for their own calculations. If a software package like Minitab is used with the course then no programming is required by the students.
A Modern Introduction to Probability and Statistics
Author: F.M. Dekking
Publisher: Springer Science & Business Media
Published: 2006-03-30
Total Pages: 488
ISBN-13: 1846281687
DOWNLOAD EBOOK →Suitable for self study Use real examples and real data sets that will be familiar to the audience Introduction to the bootstrap is included – this is a modern method missing in many other books
Probability and Statistics
Author: John Tabak
Publisher: Infobase Publishing
Published: 2014-05-14
Total Pages: 241
ISBN-13: 0816068739
DOWNLOAD EBOOK →Presents a survey of the history and evolution of the branch of mathematics that focuses on probability and statistics, including useful applications and notable mathematicians in this area.
Introduction to Probability, Statistics, and Random Processes
Author: Hossein Pishro-Nik
Publisher:
Published: 2014-08-15
Total Pages: 746
ISBN-13: 9780990637202
DOWNLOAD EBOOK →The book covers basic concepts such as random experiments, probability axioms, conditional probability, and counting methods, single and multiple random variables (discrete, continuous, and mixed), as well as moment-generating functions, characteristic functions, random vectors, and inequalities; limit theorems and convergence; introduction to Bayesian and classical statistics; random processes including processing of random signals, Poisson processes, discrete-time and continuous-time Markov chains, and Brownian motion; simulation using MATLAB and R.
Probability and Statistics with Reliability, Queuing, and Computer Science Applications
Author: Kishor S. Trivedi
Publisher: John Wiley & Sons
Published: 2016-06-30
Total Pages: 880
ISBN-13: 1119314208
DOWNLOAD EBOOK →An accessible introduction to probability, stochastic processes, and statistics for computer science and engineering applications Second edition now also available in Paperback. This updated and revised edition of the popular classic first edition relates fundamental concepts in probability and statistics to the computer sciences and engineering. The author uses Markov chains and other statistical tools to illustrate processes in reliability of computer systems and networks, fault tolerance, and performance. This edition features an entirely new section on stochastic Petri nets—as well as new sections on system availability modeling, wireless system modeling, numerical solution techniques for Markov chains, and software reliability modeling, among other subjects. Extensive revisions take new developments in solution techniques and applications into account and bring this work totally up to date. It includes more than 200 worked examples and self-study exercises for each section. Probability and Statistics with Reliability, Queuing and Computer Science Applications, Second Edition offers a comprehensive introduction to probability, stochastic processes, and statistics for students of computer science, electrical and computer engineering, and applied mathematics. Its wealth of practical examples and up-to-date information makes it an excellent resource for practitioners as well. An Instructor's Manual presenting detailed solutions to all the problems in the book is available from the Wiley editorial department.
Probability With a View Towards Statistics, Volume II
Author: J. Hoffman-Jorgensen
Publisher: Routledge
Published: 2017-11-22
Total Pages: 296
ISBN-13: 1351421549
DOWNLOAD EBOOK →Volume II of this two-volume text and reference work concentrates on the applications of probability theory to statistics, e.g., the art of calculating densities of complicated transformations of random vectors, exponential models, consistency of maximum estimators, and asymptotic normality of maximum estimators. It also discusses topics of a pure probabilistic nature, such as stochastic processes, regular conditional probabilities, strong Markov chains, random walks, and optimal stopping strategies in random games. Unusual topics include the transformation theory of densities using Hausdorff measures, the consistency theory using the upper definition function, and the asymptotic normality of maximum estimators using twice stochastic differentiability. With an emphasis on applications to statistics, this is a continuation of the first volume, though it may be used independently of that book. Assuming a knowledge of linear algebra and analysis, as well as a course in modern probability, Volume II looks at statistics from a probabilistic point of view, touching only slightly on the practical computation aspects.
All of Statistics
Author: Larry Wasserman
Publisher: Springer Science & Business Media
Published: 2013-12-11
Total Pages: 446
ISBN-13: 0387217363
DOWNLOAD EBOOK →Taken literally, the title "All of Statistics" is an exaggeration. But in spirit, the title is apt, as the book does cover a much broader range of topics than a typical introductory book on mathematical statistics. This book is for people who want to learn probability and statistics quickly. It is suitable for graduate or advanced undergraduate students in computer science, mathematics, statistics, and related disciplines. The book includes modern topics like non-parametric curve estimation, bootstrapping, and classification, topics that are usually relegated to follow-up courses. The reader is presumed to know calculus and a little linear algebra. No previous knowledge of probability and statistics is required. Statistics, data mining, and machine learning are all concerned with collecting and analysing data.
A Course in Probability and Statistics
Author: Charles J. Stone
Publisher: Duxbury Resource Center
Published: 1996
Total Pages: 858
ISBN-13:
DOWNLOAD EBOOK →This author's modern approach is intended primarily for honors undergraduates or undergraduates with a good math background taking a mathematical statistics or statistical inference course. The author takes a finite-dimensional functional modeling viewpoint (in contrast to the conventional parametric approach) to strengthen the connection between statistical theory and statistical methodology.
Fundamentals of Statistics with Fuzzy Data
Author: Hung T. Nguyen
Publisher: Springer
Published: 2006-02-28
Total Pages: 0
ISBN-13: 3540316973
DOWNLOAD EBOOK →This book presents basic aspects for a theory of statistics with fuzzy data, together with a set of practical applications. Theories of fuzzy logic and of random closed sets are used as basic ingredients in building statistical concepts and procedures in the context of imprecise data, including coarse data analysis. The book aims at motivating statisticians to examine fuzzy statistics to enlarge the domain of applicability of statistics in general.
