Introduction to data analysis and graphical presentation in biostatistics with R [electronic resource] : statistics in the large / Thomas W. MacFarland.
MacFarland, Thomas W., author.
2014
QH323.5
Available Online

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Title Introduction to data analysis and graphical presentation in biostatistics with R [electronic resource] : statistics in the large / Thomas W. MacFarland.
Author MacFarland, Thomas W., author.
ISBN 9783319025322 electronic book
3319025325 electronic book
9783319025315
DOI https://doi.org/10.1007/978-3-319-02532-2
Published Cham : Springer, 2014.
Language English
Description 1 online resource (vii, 167 pages) : illustrations (some color).
Item Number 10.1007/978-3-319-02532-2 doi
Call Number QH323.5
Dewey Decimal Classification 570.1/5195
Summary Through real-world datasets, this book shows the reader how to work with material in biostatistics using the open source software R. These include tools that are critical to dealing with missing data, which is a pressing scientific issue for those engaged in biostatistics. Readers will be equipped to run analyses and make graphical presentations based on the sample dataset and their own data. The hands-on approach will benefit students and ensure the accessibility of this book for readers with a basic understanding of R. Topics include: an introduction to Biostatistics and R, data exploration, descriptive statistics and measures of central tendency, t-Test for independent samples, t-Test for matched pairs, ANOVA, correlation and linear regression, and advice for future work.
Access Note Access limited to authorized users.
Source of Description Description based on online resource; title from PDF title page (SpringerLink, viewed November 18, 2013).
Series SpringerBriefs in statistics, 2191-544X
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Record Appears in Online Resources > Ebooks
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Introduction to Biostatistics and R
Data exploration, descriptive statistics and measures of central tendency
Student's t-Test for independent samples
Student's t-Test for matched pairs
One way ANOVA
Two way ANOVA
Correlation and linear regression
Future Actions and Next Steps.

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