Peter Flom, Significance
"This book by David Cox and Christl Donnelly, Principles of Applied Statistics, is an extensive coverage of all the necessary steps and precautions one must go through when contemplating applied (i.e. real!) statistics. ... It constitutes a magnificent testimony to the depth and to the spectrum of our field."
Christian Robert, Xi'an's Og full review
"Principles of Applied Statistics by D. R. Cox and Christl A. Donnelly takes on arguably the most important element of statistical analysis. The authors address the fundamental question of how data analysis methods can be utilized so that when statistical techniques are applied, they yield accurate and useful inferences... Cox and Donnelly have successfully walked a tightrope between being too technical for the beginner and including enough sophistication for the advanced reader. An exceptional feature of their text is the large number of applied and interesting examples, which makes sometimes subtle statistical concepts accessible to a wide audience.... This book will be useful to persons with little experience with statistical methods as a guide to analytic strategies. Equally, for those familiar with statistical methods, the material is a clear and concise reminder of the critical importance of considerations beyond the technical assumptions necessary to apply statistical techniques."
Steve Selvin, American Journal of Epidemiology
"a valuable distillation of his experience of applied work. It stands as a summary of an entire tradition of using statistics to address scientific problems. If you do not have a few years to spend apprenticed to a master, I can think of few better ways of being initiated into that tradition than reading Principles of Applied Statistics."
Cosma Shalizi, American Scientist
"Overall this book provides very clear coverage of the non-technical aspects of statistical practice: a superb outline of the meta-level issues of actually analyzing data and answering statistical questions. It would provide an ideal complement to the more traditional courses to which statistics students are exposed. And-I cannot resist-should anyone still require convincing, it demonstrates perfectly that statistics is not merely a branch of mathematics."
David J. Hand, Imperial College for International Statistical Review