Introduction to Data Analysis and Graphical Presentation in Biostatistics with R: Statistics in the Large

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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.

Author(s): Thomas W. MacFarland (auth.)
Series: SpringerBriefs in Statistics
Edition: 1
Publisher: Springer International Publishing
Year: 2014

Language: English
Pages: 167
Tags: Statistics for Life Sciences, Medicine, Health Sciences; Statistics and Computing/Statistics Programs

Front Matter....Pages i-vii
Introduction: Biostatistics and R....Pages 1-4
Data Exploration, Descriptive Statistics, and Measures of Central Tendency....Pages 5-16
Student’s t-Test for Independent Samples....Pages 17-46
Student’s t-Test for Matched Pairs....Pages 47-72
Oneway Analysis of Variance (ANOVA)....Pages 73-97
Twoway Analysis of Variance (ANOVA)....Pages 99-127
Correlation and Linear Regression....Pages 129-163
Future Actions and Next Steps....Pages 165-167