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Preface

WHY IS THIS BOOK NEEDED?

Worldwide, there is no basic statistics textbook that provides examples relevant to nutrition and dietetics. While it could be argued that general medical science statistics texts address the needs of nutrition and dietetics students, it is clear that students find it easier to take on board the concepts relating to statistical analysis and research if the examples are drawn from their own area of study. Many books also make basic assumptions about students' backgrounds that may not always be appropriate, and use statistical jargon that can be very off‐putting for students who are coming to statistics for the first time.

WHO IS THIS BOOK FOR?

The book is aimed at undergraduate and postgraduate students studying nutrition and dietetics, as well as their tutors and lecturers. In addition, there are many researchers in nutrition and dietetics who apply basic statistical techniques in the analysis of their data, for whom a basic textbook provides useful guidance, and which helps to refresh their university learning in this area with examples relevant to their own field.

LEVEL AND PRE‐REQUISITE

The level of the material is basic. It is based on a course that I taught at King's College London over many years to nutrition and dietetics students, physiotherapists, nurses, and medical students. One of the aims was to take the fear and boredom out of statistics. I did away with exams, and assessed understanding through practical exercises and coursework.

This book takes you only to the foothills of statistical analysis. A reasonable competence with arithmetic and a little algebra are required. For the application of more demanding and complex statistical techniques, the help of a statistician will be needed. Once you have mastered the material in this book, you may want to attempt a more advanced course on statistics.

AIMS AND SCOPE

The aim of this book is to provide clear, uncomplicated explanations and examples of statistical concepts and techniques for data analysis relevant to learning and research in nutrition and dietetics. There are lots of short, practical exercises to work through. These support insight into why various tests work. There are also examples of SPSS¹ output for each test. This makes it is possible to marry up the outcomes computed manually with those produced by the computer. Examples are taken from around the globe relating to all aspects of nutrition, from biochemical experiments to public health nutrition, and from clinical and community practice in dietetics. All of this is complemented by material online, including data sets ready for analysis, so that students can begin to understand how to generate and interpret SPSS output more clearly.

The book focuses on quantitative analysis. Qualitative analysis is highly valuable, but uses different approaches to data collection, analysis, and interpretation. There is an element of overlap, for example when quantitative statistical approaches are used to assess opinion data collected using questionnaires. But the two approaches have different underlying principles regarding data collection and analysis. They complement one another, but cannot replace one another.

Two things this book is not. First, it is not a ‘cookbook’ with formulas. Learning to plug numbers in to formulas by rote does not provide insight into why and how statistical tests work. Such books are good for reminding readers of the formulas which underlie the tests, but useless at conveying the necessary understanding to analyze data properly or read the scientific literature intelligently. Second, it is not a course in SPSS or Excel. While SPSS and Excel are used to provide examples of output (with some supporting syntax for clarity), it is no substitute for a proper course in computer‐based statistical analysis.

Scope

The book provides:

 a basic introduction to the scientific method

 an understanding of populations and samples, principles of measurement, and confidence intervals

 an understanding of the basic theory underlying basic statistical tests, including ‘parametric’ tests (those intended for use with data that follow mathematically defined distributions such as the so‐called ‘normal’ distribution); and ‘non‐parametric’ tests, for use with data distributions that are not parametric

 lots of worked examples and exercises that show how to compute the relevant outcome measures for each test, both by hand and using SPSS

 real examples from the nutrition and dietetics literature, including biochemical, clinical, and population‐based examples

 principles of research design, transformations, the relevance of sample size, and the concept and calculation of Power

All of the exercises have worked solutions.

Some students say, ‘Why do we have to do the exercises by hand when the computer can do the same computations in a fraction of a second?’ The answer is: computers are stupid. The old adage ‘garbage in, garbage out’ means that if you don’t have insight into why certain tests work the way they do, a computer will generate output that might be meaningless, but it won’t tell you that you’ve made a mistake, or ask ‘Is this really what you wanted to do?’ So, the purpose of the textbook and supporting learning materials is to help ensure that when you do use a computer, what goes in isn’t garbage, and what comes out is correct and provides meaningful answers to your research questions that you can interpret intelligently.

Finally, it is worth saying that some students will find this textbook providing welcome explanations about why things work the way they do. Others will find it annoyingly slow and detailed, with too much explanation for concepts and applications that seem readily apparent. If you are in the first group, I hope you enjoy the care with which explanations and examples are presented and that it helps to demystify what may at first seem a difficult topic. If you are in the second group, read quickly to get to the heart of the matter, and look for other references and resources for material that you feel is better suited to what you want to achieve. However hard or easy the text seems, students in both groups should seek to make friends with a local statistician or tutor experienced in statistical analysis and not try and do it alone.

Unique features

There are many unique features in this textbook and supporting material:

 Examples specific to nutrition and dietetics

 Clear simple language for students unfamiliar with statistical terms and approaches. For many students, the study of statistics is seen as either a burden or irrelevant to their decision to study nutrition and/or dietetics. But they will be required to pass a statistics module as part of their course. The aim is to make this as engaging and painless as possible.

 Lots of worked examples, with examples of SPSS output to help students with the interpretation of their analyses in the future.

 Putting statistics into context so that it is relevant to many undergraduate and postgraduate research projects.

 A website that provides complementary exercises, data sets, and learning and teaching tools and resources for both students and tutors.

CONTENTS

This textbook is based on over 20 years of teaching experience. There are four parts:

Part 1: Setting the statistical scene

This introduces concepts related to the scientific method and approaches to research; populations and samples; principles of measurement; probability and types of distribution of observations; and the notion of statistical testing.

Part 2: Statistical tests

This covers the basic statistical tests for data analysis. For each test, the underlying theory is explained, and practical examples are worked through, complemented by interpretation of SPSS output.

Part 3: Doing research

Most undergraduate and postgraduate courses require students to collect data and/or interpret existing data sets. This section places the concepts in Part 1 and the learning in Part 2 into a framework to help you design studies, and determine sample size and the strength of a study to test your hypothesis (‘Power’). A Flow Chart helps you select the appropriate statistical test for a given study design.

The last chapter explores briefly how to present findings to different audiences – what you say to a group of parents in a school should differ in language and visual aids from a presentation to a conference of your peers.

Part 4: Solutions to exercises

It would be desperately unfair of me to set exercises at the end of each chapter and not provide the solutions. Sometimes the solutions are obvious. Other times, you will find a commentary about why the solution is what it is, and not something else.

ONLINE

No textbook is complete these days without online resources that students and tutors can access. For this textbook, the online elements include:

 Teaching toolsTeaching notesPowerPoint slides for each chapterSPSS data, syntax, and output files

 Learning resources:Links to online software and websites that support learning about statistics and use of statistical software

TEACHING TOOLS

Teaching notes

For lecturers delivering courses based on the textbook, I have prepared brief teaching notes. These outline the approach taken to teach the concepts set out in the textbook. I used traditional lecturing coupled with in‐class work, practical exercises, homework, and research protocol development. My current practice is to avoid exams for any of this material. Exams and formal tests tend to distract students from revision of study materials more central to their course. Some students get completely tied up in knots about learning stats, and they fret about not passing the exam, ultimately to their academic disadvantage.

PowerPoint slide sets

The principal aid for tutors and lecturers is slide sets in PowerPoint. These save hours of preparation, provide consistent format of presentation, and build on approaches that have worked well with literally thousands of students that have taken these courses. When using the slides outside the context of teaching based on the text book, please ensure that you cite the source of the material.

SPSS data, syntax, and output files

A complete set of SPSS files for the examples and exercises in the text book is provided.

Learning resources

The page on Learning Resources includes website links and reviews of the strengths of a number of sites that I like and find especially helpful.

Unsurprisingly, there is a wealth of websites that support learning about statistics. Some focus on the basics. These are mainly notes from University courses that have been made available to students online. Some are good, some are not so good. Many go beyond the basics presented in this text book. Diligent searching by the student (or tutor) will no doubt unearth useful material. This will be equivalent to perusing the reading that I outline in the Introduction to Chapter 1.

Flow Charts are useful to find the statistical test that best fits the data. Appendix A10 in this book shows one. There are more online. Two that I like are described in more detail on the Learning Resources page. I have also included links to sites for determining Power and sample size.

Finally, guidance on the use of Excel and SPSS in statistics is very helpful. There are many sites that offer support, but my favourites are listed on the Learning Resources page.

Note

1 1 SPSS stands for ‘Statistical Package for the Social Sciences’. It was developed at Stamford University in California, and the first manual was authored by Norman Nie, Dale Bent, and Hadlai Hull in 1970. The package was bought in 2009 by IBM. The worked examples and syntax in this book are based on Version 24 (2016). It has come a long way since its first incarnation, in terms of ease of use, error trapping, and output. Be grateful.