A biostatistics toolbox for data analysis / Steve Selvin, University of California, Berkeley.

By:

Selvin, S [author.]

Material type: Text

TextPublisher: Cambridge : Cambridge University Press, 2015Description: 1 online resource (xvii, 560 pages) : digital, PDF file(s)Content type:

text

Media type:

computer

Carrier type:

online resource

ISBN:

9781316286159 (ebook)

Subject(s):

Additional physical formats: Print version: : No titleDDC classification:

610.2/1 23

LOC classification:

RA409 .S327 2015

Online resources:

Click here to access online

Summary: This sophisticated package of statistical methods is for advanced master's (MPH) and PhD students in public health and epidemiology who are involved in the analysis of data. It makes the link from statistical theory to data analysis, focusing on the methods and data types most common in public health and related fields. Like most toolboxes, the statistical tools in this book are organized into sections with similar objectives. Unlike most toolboxes, however, these tools are accompanied by complete instructions, explanations, detailed examples, and advice on relevant issues and potential pitfalls - conveying skills, intuition, and experience.

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Holdings
Item type	Current library	Collection	Call number	Status	Date due	Barcode
eBooks	Central Library	Statistics & Probability		Available		EB0007

This sophisticated package of statistical methods is for advanced master's (MPH) and PhD students in public health and epidemiology who are involved in the analysis of data. It makes the link from statistical theory to data analysis, focusing on the methods and data types most common in public health and related fields. Like most toolboxes, the statistical tools in this book are organized into sections with similar objectives. Unlike most toolboxes, however, these tools are accompanied by complete instructions, explanations, detailed examples, and advice on relevant issues and potential pitfalls - conveying skills, intuition, and experience.

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A biostatistics toolbox for data analysis / Steve Selvin, University of California, Berkeley.