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Many of the actions performed from by a statistical software comes back to handle,down to manipulating or even transforming digital data, which actually representing statistical data literally.It is therefore of primary importance to understand how the statisticsal data are displayed and how they can be exploited by software such as R. The authors explore basic and variable commands, sample comparisons, analysis of variance, epidemiological studies and censored data.With proposed applications and examples of commands following each chapter, this book allows you to apply advanced statistical concepts to your own data and software. This book features: Useful commands for describing a data table composed made up of quantitative and qualitative variablesMeasures of association encountered in epidemiological studies: odds ratio, relative risk, prevalenceAnalysis of censored data, the key main tests associated with the construction of a survival curve (log-rank test or Wilcoxon) and the Cox regression model