University of Pittsburgh, Pittsburgh, PA University of Bath, UK University of Minnesota, Minneapolis, USA Northwestern University, Evanston, Illinois, USA University of British Columbia, Vancouver, Canada

• Review of Topics in Probability and Statistics. Use of Simulation Techniques. The Central Limit Theorem. Correlation and Regression. Analysis of Variance. Discrete Measures of Risk. Multivariate Analysis. Analysis of Repeated Measures Data. Nonparametric Methods. Analysis of Time to Event Data. Sample Size and Power Calculations. Appendices. References. Index.

"The book presents important topics in biostatistics alongside examples provided in the programming languages SAS and R. … The book covers many relevant topics every student should know in a way that it makes it easy to follow … each chapter provides exercises encouraging the reader to deepen her/his understanding. I really like that the theory is presented in a clear manner without interruptions of example programs. Instead, the programs are always presented at the end of a section. … this book can serve as a good start for the more statistics inclined students who haven’t yet recognized that in order to become a good biostatistician, you need to be able to write your own code. … I can recommend to all serious students who want to get a thorough start into this field."—Frank Emmert-Streib, Queen’s University Belfast, CHANCE, August 2013

University of Pittsburgh, Pittsburgh, PA University of Bath, UK University of Minnesota, Minneapolis, USA Northwestern University, Evanston, Illinois, USA University of British Columbia, Vancouver, Canada

• Review of Topics in Probability and Statistics. Use of Simulation Techniques. The Central Limit Theorem. Correlation and Regression. Analysis of Variance. Discrete Measures of Risk. Multivariate Analysis. Analysis of Repeated Measures Data. Nonparametric Methods. Analysis of Time to Event Data. Sample Size and Power Calculations. Appendices. References. Index.

"The book presents important topics in biostatistics alongside examples provided in the programming languages SAS and R. … The book covers many relevant topics every student should know in a way that it makes it easy to follow … each chapter provides exercises encouraging the reader to deepen her/his understanding. I really like that the theory is presented in a clear manner without interruptions of example programs. Instead, the programs are always presented at the end of a section. … this book can serve as a good start for the more statistics inclined students who haven’t yet recognized that in order to become a good biostatistician, you need to be able to write your own code. … I can recommend to all serious students who want to get a thorough start into this field."—Frank Emmert-Streib, Queen’s University Belfast, CHANCE, August 2013

University of Pittsburgh, Pittsburgh, PA University of Bath, UK University of Minnesota, Minneapolis, USA Northwestern University, Evanston, Illinois, USA University of British Columbia, Vancouver, Canada

• Review of Topics in Probability and Statistics. Use of Simulation Techniques. The Central Limit Theorem. Correlation and Regression. Analysis of Variance. Discrete Measures of Risk. Multivariate Analysis. Analysis of Repeated Measures Data. Nonparametric Methods. Analysis of Time to Event Data. Sample Size and Power Calculations. Appendices. References. Index.

"The book presents important topics in biostatistics alongside examples provided in the programming languages SAS and R. … The book covers many relevant topics every student should know in a way that it makes it easy to follow … each chapter provides exercises encouraging the reader to deepen her/his understanding. I really like that the theory is presented in a clear manner without interruptions of example programs. Instead, the programs are always presented at the end of a section. … this book can serve as a good start for the more statistics inclined students who haven’t yet recognized that in order to become a good biostatistician, you need to be able to write your own code. … I can recommend to all serious students who want to get a thorough start into this field."—Frank Emmert-Streib, Queen’s University Belfast, CHANCE, August 2013