Choosing and Using Statistics: A Biologist's Guide
Dytham, Calvin
Used - Soft cover
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Add to basketCondition: Used - Good
Quantity: 1 available
Add to basketBefriedigend/Good: Durchschnittlich erhaltenes Buch bzw. Schutzumschlag mit Gebrauchsspuren, aber vollständigen Seiten. / Describes the average WORN book or dust jacket that has all the pages present.
Seller Inventory # M01405102438-G
This is a book for any student or professional biologist who wants to process data using a statistical package on the computer, to select appropriate methods, and extract the important information from the often confusing output that is produced. It is aimed primarily at undergraduates and masters students in the biological sciences who have to apply statistics in practical classes and projects. Such users of statistics do not have to understand either how tests work or how to do the calculations, and these aspects are not covered in the book.
The new edition has been updated to cover the very latest versions of the computer packages described, expanded to include coverage for logistic regression, a more detailed consideration of multivariate analysis, data exploration and further examples of Principle Component Analysis and Discriminate Function Analysis are given.
This is a book for any student or professional biologist who wants to process data using a statistical package on the computer, to select appropriate methods, and extract the important information from the often confusing output that is produced. It is aimed primarily at undergraduates and masters students in the biological sciences who have to apply statistics in practical classes and projects. Such users of statistics do not have to understand either how tests work or how to do the calculations, and these aspects are not covered in the book.
The new edition has been updated to cover the very latest versions of the computer packages described, expanded to include coverage for logistic regression, a more detailed consideration of multivariate analysis, data exploration and further examples of Principle Component Analysis and Discriminate Function Analysis are given.
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