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.
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.
From the book reviews:
"This text serves as an introduction to the use of R in biostatistics. It has specifically been structured to demonstrate the use of R syntax as opposed to the use of a point-and-select graphical user interface. ... Small and easy-to-follow confidence-building examples have been used throughout this text. ... This monograph is very useful not only for students in informatics, but especially also for those in medicine and biology related with the courses in biostatistics (medical statistics) and bioinformatics." (T. Postelnicu, zbMATH 1306.62016, 2015)
"This text serves as an introduction to the use of R in biostatistics. It has specifically been structured to demonstrate the use of R syntax as opposed to the use of a point-and-select graphical user interface. ... Small and easy-to-follow confidence-building examples have been used throughout this text. ... This monograph is very useful not only for students in informatics, but especially also for those in medicine and biology related with the courses in biostatistics (medical statistics) and bioinformatics." (T. Postelnicu, zbMATH 1306.62016, 2015)