
- 224 pages
- English
- ePUB (mobile friendly)
- Available on iOS & Android
Basic Concepts in Statistics and Epidemiology
About this book
This book contains a Foreword by Allyson Pollock, Professor and Head, Centre for International Public Health Policy, University of Edinburgh. Healthcare students, practitioners and researchers need a sound basis for making valid statistical inferences from health data. To make the best use of statistical software, it is necessary to understand how probabilistic inference works. This book explains that, along with the various ways statistical data can be described and presented. It is designed to develop insight rather than simply the mechanical skills found in other textbooks. This book is specifically designed to underpin the concepts of statistics and epidemiology. It is practical and easy to use and is ideal for people who can feel uncomfortable with mathematics. 'Excellent. A great primer for all students and research workers engaged in learning how to use statistical ideas in public health. It sets out the core concepts and explains them clearly, using worked examples as illustration. If followed carefully, the engaged reader should be able to use the standard statistical software packages intelligently and sensitively. It will stimulate the public health student, in whatever context, and new researchers, to approach the enterprise with enhanced confidence in interpreting and coherently explaining their findings.' - Allyson Pollock, in the Foreword.
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Information
Table of contents
- Cover Page
- Halftitle Page
- Copyright Page
- Contents
- Foreword
- Preface
- Acknowledgements
- Chapter 1: Describing a mass of data
- Chapter 2: A necessary glimpse of probability
- Chapter 3: Using the normal curve
- Chapter 4: An approximation to the normal curve
- Chapter 5: Testing samples
- Chapter 6: Testing small samples
- Chapter 7: A taste of epidemiology
- Chapter 8: From binomial to Poisson
- Chapter 9: Non-parametric statistics
- Chapter 10: For the algebraically innocent
- Chapter 11: The Gini coefficient
- Chapter 12: Correlation a measure of relatedness
- Chapter 13: The problem of prediction
- Chapter 14: Introducing ANOVA
- Chapter 15: A brief introduction to designing a research project
- Appendix
- Appendix
- Appendix
- Appendix
- Appendix
- Appendix
- Appendix
- Appendix
- Appendix
- Appendix
- Index