Go back

Computational Statistics Volume 1(1st Edition)

Authors:

Yadolah Dodge, Joe Whittaker

Free computational statistics volume 1 1st edition yadolah dodge, joe whittaker 3662268132, 978-3662268131
4 ratings
Cover Type:Hardcover
Condition:Used

In Stock

Shipment time

Expected shipping within 2 Days
Access to 30 Million+ solutions Free
Ask 50 Questions from expert AI-Powered Answers
7 days-trial

Total Price:

$0

List Price: $145.60 Savings: $145.6(100%)
Access to 30 Million+ solutions
Ask 50 Questions from expert AI-Powered Answers 24/7 Tutor Help Detailed solutions for Computational Statistics Volume 1

Price:

$9.99

/month

Book details

ISBN: 3662268132, 978-3662268131

Book publisher: Physica

Get your hands on the best-selling book Computational Statistics Volume 1 1st Edition for free. Feed your curiosity and let your imagination soar with the best stories coming out to you without hefty price tags. Browse SolutionInn to discover a treasure trove of fiction and non-fiction books where every page leads the reader to an undiscovered world. Start your literary adventure right away and also enjoy free shipping of these complimentary books to your door.

Book Summary: The Role of the Computer in Statistics David Cox Nuffield College, Oxford OXIINF, U.K. A classification of statistical problems via their computational demands hinges on four components (I) the amount and complexity of the data, (il) the specificity of the objectives of the analysis, (iii) the broad aspects of the approach to analysis, (ill) the conceptual, mathematical and numerical analytic complexity of the methods. Computational requi­ rements may be limiting in (I) and (ill), either through the need for special programming effort, or because of the difficulties of initial data management or because of the load of detailed analysis. The implications of modern computational developments for statistical work can be illustrated in the context of the study of specific probabilistic models, the development of general statistical theory, the design of investigations and the analysis of empirical data. While simulation is usually likely to be the most sensible way of investigating specific complex stochastic models, computerized algebra has an obvious role in the more analyti­ cal work. It seems likely that statistics and applied probability have made insufficient use of developments in numerical analysis associated more with classical applied mathematics, in particular in the solution of large systems of ordinary and partial differential equations, integral equations and integra-differential equations and for the ¢raction of "useful" in­ formation from integral transforms. Increasing emphasis on models incorporating specific subject-matter considerations is one route to bridging the gap between statistical ana.­