MOMENTAN AUSVERKAUFT
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Product Identifiers
PublisherFreeman & Company, W&H
ISBN-100716747421
ISBN-139780716747420
eBay Product ID (ePID)6042381
Product Key Features
Number of Pages638 Pages
LanguageEnglish
Publication NameProbability and Statistics : the Science of Uncertainty
SubjectProbability & Statistics / General
Publication Year2003
TypeTextbook
AuthorMichael J. Evans, Jeffrey S. Rosenthal
Subject AreaMathematics
FormatHardcover
Dimensions
Item Height1.4 in
Item Weight43.8 Oz
Item Length9.6 in
Item Width7.2 in
Additional Product Features
Intended AudienceCollege Audience
LCCN2003-108117
Dewey Edition22
IllustratedYes
Dewey Decimal519.2
Table Of Content1. Probability Models 2. Random Variables and Distributions 3. Expectation 4. Sampling Distributions and Limits 5. Statistical Inference 6. Likelihood Inference 7. Bayesian inference 8. Optimal Inferences 9. Model Checking 10. Relationships Among Variables 11. Advance TopicStochastic Processes Appendices Index
SynopsisUnlike 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.
LC Classification NumberQA273
