Probability : With Applications and R

Amy S Wagaman

ISBN 10: 1119692385 / ISBN 13: 9781119692386

Published by Wiley Jul 2021, 2021

About this Item

Neuware - Discover the latest edition of a practical introduction to the theory of probability, complete with R code samplesIn the newly revised Second Edition of Probability: With Applications and R, distinguished researchers Drs. Robert Dobrow and Amy Wagaman deliver a thorough introduction to the foundations of probability theory. The book includes a host of chapter exercises, examples in R with included code, and well-explained solutions. With new and improved discussions on reproducibility for random numbers and how to set seeds in R, and organizational changes, the new edition will be of use to anyone taking their first probability course within a mathematics, statistics, engineering, or data science program.New exercises and supplemental materials support more engagement with R, and include new code samples to accompany examples in a variety of chapters and sections that didn't include them in the first edition.The new edition also includes for the first time:\* A thorough discussion of reproducibility in the context of generating random numbers\* Revised sections and exercises on conditioning, and a renewed description of specifying PMFs and PDFs\* Substantial organizational changes to improve the flow of the material\* Additional descriptions and supplemental examples to the bivariate sections to assist students with a limited understanding of calculusPerfect for upper-level undergraduate students in a first course on probability theory, Probability: With Applications and R is also ideal for researchers seeking to learn probability from the ground up or those self-studying probability for the purpose of taking advanced coursework or preparing for actuarial exams.

Seller Inventory # 9781119692386

Bibliographic Details

• Title: Probability : With Applications and R
• Publisher: Wiley Jul 2021
• Publication Date: 2021
• Language: English
• ISBN 10: 1119692385
• ISBN 13: 9781119692386
• Binding: Buch
• Edition: 2nd Edition
• Condition: Neu
• Dimensions: 229W x 152H x 30D millimeters 229 millimeters width by 152 millimeters height by 30 millimeters depth
• Weight: 894 grams

About this title

Synopsis

Discover the latest edition of a practical introduction to the theory of probability, complete with R code samples

In the newly revised Second Edition of Probability: With Applications and R, distinguished researchers Drs. Robert Dobrow and Amy Wagaman deliver a thorough introduction to the foundations of probability theory. The book includes a host of chapter exercises, examples in R with included code, and well-explained solutions. With new and improved discussions on reproducibility for random numbers and how to set seeds in R, and organizational changes, the new edition will be of use to anyone taking their first probability course within a mathematics, statistics, engineering, or data science program.

New exercises and supplemental materials support more engagement with R, and include new code samples to accompany examples in a variety of chapters and sections that didn’t include them in the first edition.

The new edition also includes for the first time: 

• A thorough discussion of reproducibility in the context of generating random numbers
• Revised sections and exercises on conditioning, and a renewed description of specifying PMFs and PDFs
• Substantial organizational changes to improve the flow of the material
• Additional descriptions and supplemental examples to the bivariate sections to assist students with a limited understanding of calculus

Perfect for upper-level undergraduate students in a first course on probability theory, Probability: With Applications and R is also ideal for researchers seeking to learn probability from the ground up or those self-studying probability for the purpose of taking advanced coursework or preparing for actuarial exams.

About the Author

Amy S. Wagaman, PhD, is Associate Professor of Statistics at Amherst College. She received her doctorate in Statistics at the University of Michigan in 2008. Her research interests include nonparametric statistics, statistics education, dimension reduction and estimation, and covariance estimation and regularization.

Robert P. Dobrow, PhD, is Emeritus Professor of Mathematics at Carleton College. He has over 15 years of experience teaching probability and has authored numerous papers in probability theory, Markov chains, and statistics.