Preface

Today, externally funded research is the rule rather than the exception. The problem statements and hypotheses of a research project have already been formulated by a senior researcher when filing the funding application. When the research student enters the picture a project plan has already been made. All that remains is to produce results in the laboratory. This situation enhances the impression that many students have, that experiments are mainly about taking measurements – a belief arising during traditional, structured laboratory classes that are based on demonstrations rather than real experiments.

Experienced experimenters know that the main efforts in a successful experiment lie in meticulous planning and analysis, and that both of these must be firmly rooted in a scientific approach. Entering the research process at such a late stage, students may be delayed in realizing this crucial point. The art of experimentation is often learned by doing, so an intuitive understanding of the experimental method usually evolves gradually during years of trial and error. The aim of this book is to speed up the journey.

Research education is often practically oriented, focusing on techniques and concepts that are used in specific research areas. In order to become an independent researcher it is important to also acquire more general research competencies. Research students must adopt a scientific mindset, learn how to plan meaningful experiments, and understand the fundamentals of collecting and interpreting data. This book focuses on these general research skills. It is directed to anyone engaged in experiments, and especially Ph.D. and master’s students just starting to develop their own experiments.

There are several books that discuss the scientific method from a philosophical standpoint. There are also good books covering research methods from a statistical point of view. Why do we need another book on scientific method? The reason is that scientists need to employ several types of research competency in parallel, and it is unfortunate that these tend to be taught separately. The philosophy of science is frequently introduced using historical examples in courses where more time is spent criticizing ideas than explaining how to apply them. It is too common to teach statistics as a pure study of numbers without explaining how numbers may be turned into meaningful scientific knowledge. The lack of a context relevant to working scientists makes it difficult for research students to incorporate such knowledge into their other research competencies. This book aims to merge these aspects of research into a practically workable package.

The book is organized in two parts. The first part gives a general introduction to the scientific approach while the second describes general methods and tools with a focus on experiments. Towards the end of the book a methodology is presented, which leads the reader through the three phases of an experiment: “Planning”, “Data Collection”, and “Analysis and Synthesis”. The first phase puts the discussion about scientific and experimental method into a practical context, treating how research problems may be identified and how to approach them by conceiving meaningful experiments. The following two phases continue to build on these ideas, but incorporate statistical techniques into the process. In the data collection phase, a measurement system is devised, analyzed and improved to obtain data of sufficient quality. In the last phase, the raw data are turned into meaningful information, analyzed with graphical and mathematical tools, and connected back to the research question.

It is my experience that this methodology helps students connect the somewhat abstract concepts from statistical theory and the philosophy of science to their scientific praxis. I am not an advocate of cookbook recipes for research and the methodology is not to be viewed that way. The idea is rather that readers, by applying these simple tools to their own research problems, will reflect on and learn to understand key elements of the experimental method.

Many people have kindly helped me in the preparation of this book. My friend and colleague Rolf Egnell deserves a very special thank you for taking the time to read and comment on the manuscript in its entirety. He has had the admirable ability to look beyond the depths of his knowledge and read the text with the eyes of a layman. His valuable comments have significantly improved the readability of this text. I am also grateful to Tim Davis for his comments on the statistics material, and to Staffan Ulfstrand for providing feedback on parts where evolutionary biology is discussed. Advice and help of various kinds were willingly given by Malte Andersson, Marie Dacke, Leif Lönnblad, Carl-Erik Magnusson, Clément Chartier, Johan Zetterberg, and Tony Greenfield. I also want to thank Sarah Tilley at Wiley in Chichester, UK, for her support and encouraging remarks along the way. I gratefully acknowledge these people while stressing that I am, of course, solely responsible for any mistakes or other authorial shortcoming still present in the text.

When writing this, others come to mind that have helped me over the years. Many have had a hand in teaching me to see the world around me and to think independently, but space prevents me from mentioning them all. I especially owe thanks to the teachers and staff at the Departments of Physics and Theoretical Physics in Lund, who always presented scientific ideas with a perfect blend of playfulness and intellectual sharpness. I am also grateful to my mother for her unconditional support in all life’s endeavors. As a child she instilled in me that I succeeded with everything I tried my hand at, even though I often did not.

Above all, my deepest and most heartfelt gratitude goes to Gunnel, the love of my life, and Carl-Johan, our son, for their sympathy, patience and laughter. You are the twin star around which my world blissfully revolves.