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Introductory applied biostatistics / Ralph B. D'Agostino, Sr., Lisa M. Sullivan, Alexa S. Beiser.

By: Contributor(s): Material type: TextTextPublication details: Belmont, CA. : Thomson, Higher Education, c2006.Description: xiii, 652 p. : ill. ; 24 cm. + 1 CD ROM (4 3/4 in.)ISBN:
  • 053442399X
Subject(s): DDC classification:
  • 570/.1/5195 22
LOC classification:
  • QH 323.5  .D134 2006
Summary: Introductory Applied Biostatistics provides a solid and engaging background for students learning to apply and appropriately interpret statistical applications in the medical and public health fields. The many examples drawn directly from the authors' remarkable clinical experiences with applied biostatistics make this text relevant, practical, and interesting for students. This flexible textbook encourages students to master application techniques by hand before moving on to computer applications, with SAS programming code and output for each technique covered in every chapter. The majority of the textbook addresses methods for statistical inference, including one- and two-sample tests for means and proportions, analysis of variance techniques, correlation, and regression analysis. For each topic, the book addresses methodology, including assumptions, statistical formulas, and appropriate interpretation of results.
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Holdings
Item type Current library Collection Call number Status Date due Barcode
Graduate Studies Graduate Studies DLSU-D GRADUATE STUDIES Graduate Studies Graduate Studies QH 323.5 .D134 2006 (Browse shelf(Opens below)) Available 3AEA0000298880

Introductory Applied Biostatistics provides a solid and engaging background for students learning to apply and appropriately interpret statistical applications in the medical and public health fields. The many examples drawn directly from the authors' remarkable clinical experiences with applied biostatistics make this text relevant, practical, and interesting for students. This flexible textbook encourages students to master application techniques by hand before moving on to computer applications, with SAS programming code and output for each technique covered in every chapter. The majority of the textbook addresses methods for statistical inference, including one- and two-sample tests for means and proportions, analysis of variance techniques, correlation, and regression analysis. For each topic, the book addresses methodology, including assumptions, statistical formulas, and appropriate interpretation of results.

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