Description
Book SynopsisEach statistical chapter in the second part relies on one or more real biomedical data sets, kindly made available by the Bordeaux School of Public Health (Institut de Santé Publique, d'Épidémiologie et de Développement - ISPED) and described at the beginning of the book.
Trade ReviewFrom the book reviews:
“This is a great addition to the chorus of books on R. It is a clear an excellent resource for teaching courses on data analysis and statistical computing using R at the graduate and advanced undergraduate levels. The book can be an asset for data scientists, and even more broadly for a wide variety of users including students, teachers, researchers, software engineers, and others whose work involves statistics, mathematics, and computer science.” (Yousri El Fattah, Computing Reviews, January, 2015)
Table of ContentsForeward.- Basic Concepts and Data Organisation.- Importing, Exporting and Producing Data.- Data Manipulation, Functions.- R and its Documentation.- Drawing Curves and Plots.- Programming in R.- Managing Sessions.- Basic Mathematics.- Descriptive Statistics.- A Better Understanding of Random Variables.- Confidence Intervals and Hypothesis Testing.- Simple and Multiple Linear Regression.- Elementary Analysis of Variance.- Installing R and R Packages.- References.- Indices.- Solutions.
