Principles of applied statistics
By: D.R. Cox, Christl A. Donnelly
Contributors: Donnelly, Christl A.
Publisher: Cambridge University Press
Published: 2011
Place of publication: Cambridge; New York
Language: eng
Number of pages: 212
ISBN-13: 9781107013599; 9781107644458
Subjects: MATHEMATICS / Probability & Statistics / General; Mathematical statistics; Statistics
Description: "Applied statistics is more than data analysis, but it is easy to lose sight of the big picture. David Cox and Christl Donnelly distil decades of scientific experience into usable principles for the successful application of statistics, showing how good statistical strategy shapes every stage of an investigation. As you advance from research or policy question, to study design, through modelling and interpretation, and finally to meaningful conclusions, this book will be a valuable guide. Over a hundred illustrations from a wide variety of real applications make the conceptual points concrete, illuminating your path and deepening your understanding. This book is essential reading for anyone who makes extensive use of statistical methods in their work"--

"In ideal sequence is defined specifying the progression of an investigation from the conception of one or more research questions to the drawing of conclusions. The role of statistical analysis is outlined for design, measurement, analysis and interpretation. 1.1 Preliminaries This short chapter gives a general account of the issues to be discussed in the book, namely those connected with situations in which appreciable unexplained and haphazard variation is present. We outline in idealized form the main phases of this kind of scientific investigation and the stages of statistical analysis likely to be needed. It would be arid to attempt a precise definition of statistical analysis as contrasted with other forms of analysis"--
Notes: Includes index.
Table of contents: title: Machine generated contents note: Preface; 1. Some general concepts; 2. Design of studies; 3. Special types of study; 4. Principles of measurement; 5. Preliminary analysis; 6. Model formulation; 7. Model choice; 8. Techniques of formal inference; 9. Interpretation; 10. Epilogue; References; Index.