Isbn: 9781466512108 - understanding advanced statistical methods (17 risultati)

Condizione: Acceptable. This book is acceptable. It is a useful copy but not pretty. There may be writing, loose pages, or a damaged cover. hardcoverUsed - Acceptable2013.

Hardcover. Condizione: New.

Condizione: New.

Condizione: As New. Unread book in perfect condition.

Condizione: As New. Unread book in perfect condition.

Condizione: New.

Hardback. Condizione: New. New copy - Usually dispatched within 4 working days.

Hardcover. Condizione: new. New Copy. Customer Service Guaranteed.

Condizione: New.

HRD. Condizione: New. New Book. Shipped from UK. Established seller since 2000.

Condizione: New. pp. 569.

Condizione: New. In English.

Condizione: New. pp. 569.

Gebunden. Condizione: New. Peter H. Westfall is the Paul Whitfield Horn Professor of Statistics and James Niver Professor of Information Systems and Quantitative Sciences at Texas Tech University. A Fellow of the ASA and the AAAS, Dr. Westfall has published severa.

Hardcover. Condizione: Brand New. 543 pages. 10.00x7.25x1.25 inches. In Stock.

Buch. Condizione: Neu. Neuware - Providing a much-needed bridge between elementary statistics courses and advanced research methods courses, Understanding Advanced Statistical Methods helps students grasp the fundamental assumptions and machinery behind sophisticated statistical topics, such as logistic regression, maximum likelihood, bootstrapping, nonparametrics, and Bayesian methods. The book teaches students how to properly model, think critically, and design their own studies to avoid common errors. It leads them to think differently not only about math and statistics but also about general research and the scientific method.With a focus on statistical models as producers of data, the book enables students to more easily understand the machinery of advanced statistics. It also downplays the 'population' interpretation of statistical models and presents Bayesian methods before frequentist ones. Requiring no prior calculus experience, the text employs a 'just-in-time' approach that introduces mathematical topics, including calculus, where needed. Formulas throughout the text are used to explain why calculus and probability are essential in statistical modeling. The authors also intuitively explain the theory and logic behind real data analysis, incorporating a range of application examples from the social, economic, biological, medical, physical, and engineering sciences.Enabling your students to answer the why behind statistical methods, this text teaches them how to successfully draw conclusions when the premises are flawed. It empowers them to use advanced statistical methods with confidence and develop their own statistical recipes. Ancillary materials are available on the book's website.…

Condizione: New. pp. 569 235 This item is printed on demand.