Data analysis lies at the heart of every experimental science. Providing a modern introduction to statistics, this book is ideal for undergraduates in physics. It introduces the necessary tools required to analyse data from experiments across a range of areas, making it a valuable resource for students. In addition to covering the basic topics, the book also takes in advanced and modern subjects, such as neural networks, decision trees, fitting techniques and issues concerning limit or interval setting. Worked examples and case studies illustrate the techniques presented, and end-of-chapter exercises help test the reader's understanding of the material.
Adrian Bevan is a Reader in Particle Physics in the School of Physics and Astronomy, Queen Mary, University of London. He is an expert in quark flavour physics and has been analysing experimental data for over 15 years.
Preface; 1. Introduction; 2. Sets; 3. Probability; 4. Visualising and quantifying the properties of data; 5. Useful distributions; 6. Uncertainty and errors; 7. Confidence intervals; 8. Hypothesis testing; 9. Fitting; 10. Multivariate analysis; Appendixes; References; Index.