Scientific Data Analysis

Description

Drawing on the author's extensive experience of supporting students undertaking projects, 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.

• The only data analysis text to both describe the principles and show the practice, combining text and video to optimum effect
• Written to be the ideal guide for students who need a step-by-step guide to carrying out the analysis of their own data
• Examples drawn from across the sciences show how data analysis applies to the reality of scientific research
• Suitable for use by students using any of the most heavily used statistics packages, with guidance covering Minitab, SPSS, and Excel
• An extensive bank of videos accompanying the text show the 'keystroke' use of analytical software when carrying out analysis in practice

About the Author(s)

Graham Currell, Formerly of the University of the West of England

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.

Table of Contents

Part I - Understanding the statistics
1:Statistical concepts
2:Regression analysis
3:Hypothesis testing
4:Comparing data
Part II - Analysing experimental data
5:Project data analysis
6:Single response variables
7:Related variables
8:Frequency data
9:Multiple variables

Reviews

"This is an appealing introduction that would be accessible to a variety of students at the college level. Its strengths are clarity and directness with an abundance of good examples and case studies." - MAA Review

Additional Resources

The text is accompanied by an Online Resource Centre that features over 80 video screencasts. These screencasts walk the viewer step-by-step through the techniques and approaches outlined in the book.