Understanding Advanced Statistical Methods Contributor(s): Westfall, Peter (Author), Henning, Kevin S. S. (Author) |
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ISBN: 1466512105 ISBN-13: 9781466512108 Publisher: CRC Press OUR PRICE: $114.00 Product Type: Hardcover - Other Formats Published: April 2013 |
Additional Information |
BISAC Categories: - Mathematics | Probability & Statistics - Bayesian Analysis |
Dewey: 519.5 |
LCCN: 2013003655 |
Series: Chapman & Hall/CRC Texts in Statistical Science |
Physical Information: 1.3" H x 7.2" W x 10.1" (2.55 lbs) 569 pages |
Descriptions, Reviews, Etc. |
Publisher Description: 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. |