9780716762195-0716762196-Probability and Statistics Solutions Manual

Probability and Statistics Solutions Manual

ISBN-13: 9780716762195
ISBN-10: 0716762196
Edition: First Edition
Author: Jeffrey S Rosenthal, Michael J. Evans
Publication date: 2006
Publisher: W. H. Freeman
Format: Paperback 200 pages
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Book details

ISBN-13: 9780716762195
ISBN-10: 0716762196
Edition: First Edition
Author: Jeffrey S Rosenthal, Michael J. Evans
Publication date: 2006
Publisher: W. H. Freeman
Format: Paperback 200 pages

Summary

Probability and Statistics Solutions Manual (ISBN-13: 9780716762195 and ISBN-10: 0716762196), written by authors Jeffrey S Rosenthal, Michael J. Evans, was published by W. H. Freeman in 2006. With an overall rating of 4.0 stars, it's a notable title among other Statistics (Education & Reference) books. You can easily purchase or rent Probability and Statistics Solutions Manual (Paperback) from BooksRun, along with many other new and used Statistics books and textbooks. And, if you're looking to sell your copy, our current buyback offer is $0.3.

Description

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.

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