Description

Book Synopsis
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.

Trade Review
'Suitable for students and researchers in public health.' MARY JANE PLATT, PUBLIC HEALTH

Table of Contents
Describing a mass of data. A necessary glimpse of probability. Using the normal curve. An approximation to the normal curve. Poisson's solution. Testing samples. Testing small samples. A taste of epidemiology. Non-parametric statistics. For the algebraically innocent. Correlation - a measure of relatedness. The problem of prediction. Introducing ANOVA. A brief introduction to designing a research project.

Basic Concepts in Statistics and Epidemiology

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    Order before 4pm today for delivery by Fri 26 Jun 2026.

    A Paperback / softback by Theodore H. MacDonald, Denis Pereira Gray

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      View other formats and editions of Basic Concepts in Statistics and Epidemiology by Theodore H. MacDonald

      Publisher: Taylor & Francis Ltd
      Publication Date: 20/12/2006
      ISBN13: 9781846191244, 978-1846191244
      ISBN10: 1846191246

      Description

      Book Synopsis
      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.

      Trade Review
      'Suitable for students and researchers in public health.' MARY JANE PLATT, PUBLIC HEALTH

      Table of Contents
      Describing a mass of data. A necessary glimpse of probability. Using the normal curve. An approximation to the normal curve. Poisson's solution. Testing samples. Testing small samples. A taste of epidemiology. Non-parametric statistics. For the algebraically innocent. Correlation - a measure of relatedness. The problem of prediction. Introducing ANOVA. A brief introduction to designing a research project.

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