Reliable data analysis lies at the heart of scientific research, helping you to figure out what your data is really telling you. Yet the analysis of data can be a stumbling block for even the most experienced researcher - and can be a particularly daunting prospect when analyzing your own data for the first time.
Drawing on the author's extensive experience of supporting project students, Scientific Data Analysis is a guide for any science undergraduate or beginning graduate who needs to analyse their own data, and wants a clear, step-by-step description of how to carry out their analysis in a robust, error-free way.
With video content generated by the author to dovetail with the printed text, the resource not only describes the principles of data analysis and the strategies that should be adopted for a successful outcome but also shows you how to carry out that analysis - with the videos breaking down the process of analysis into easy-to-digest chunks.
With guidance on the use of Minitab, SPSS and Excel, Scientific Data Analysis doesn't just support the use of one particular software package: it is the ideal guide to carrying out your own data analysis regardless of the software you have chosen.
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Until his retirement in 2009, Graham Currell was a Principal Lecturer in physics at the University of the West of England. During his early career his particular interest was in the preparation of specialist training programmes to support staff in university science laboratories in Asia, the Middle East, Africa and Central America, but since 2000 he has concentrated on the development of data analysis modules and self-study materials for science students, and until summer 2014 became a part-time research fellow, in which he further explored the development of online learning resources. This book builds on Graham's development of teaching materials for maths and statistics, including screen-capture videos in forensic, chemical, biological, and environmental science for UWE and the Royal Society of Chemistry. The approach reflects his extensive experience of providing tutorial and training support for students and staff carrying out research projects across both the physical and life sciences.
PART I - UNDERSTANDING THE STATISTICS; PART II - ANALYSING EXPERIMENTAL DATA