Statistical Research Methods in the Life Sciences
By: Rao, P. V
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Material type: 
BookPublisher: USA : Duxbury Press, 1998Edition: 1st ed.Description: 889 p.ISBN: 0534931413 (hardcover); 9780534931414 (hardcover).Subject(s): Life Science--Statistical Methods, StatisticsDDC classification: 570 Rao 17195 1st 1998 Statistics Summary: Appropriate for all courses in statistical methods for the agricultural, life, health, and environmental sciences, this book offers a practical and modern approach that minimizes computation and emphasizes conceptual understanding. Rao continually emphasizes issues and topics most relevant to modern day research in the life sciences. For example, point and interval estimation take priority over testing of statistical hypothesis and methods and guidelines for determination of sample size are indicated whenever possible. Statistical Research Methods in the Life Sciences also presents a self-contained and complete discussion of each experimental situation considered. In the two-sample setting, for example, in addition to presenting the procedures under the usual analysis of variance assumption, Rao also presents methods for checking the validity of the assumptions.
| Item type | Current location | Collection | Call number | Status | Date due | Barcode | Item holds |
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UVAS Library Statistics | Social Science | 570 Rao 17195 1st 1998 Statistics (Browse shelf) | Available | 17195 |
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Appropriate for all courses in statistical methods for the agricultural, life, health, and environmental sciences, this book offers a practical and modern approach that minimizes computation and emphasizes conceptual understanding. Rao continually emphasizes issues and topics most relevant to modern day research in the life sciences. For example, point and interval estimation take priority over testing of statistical hypothesis and methods and guidelines for determination of sample size are indicated whenever possible. Statistical Research Methods in the Life Sciences also presents a self-contained and complete discussion of each experimental situation considered. In the two-sample setting, for example, in addition to presenting the procedures under the usual analysis of variance assumption, Rao also presents methods for checking the validity of the assumptions.
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