Physics 390 - Autumn 2012

Computer Assisted Data Analysis in Physics


V. Erkcan Özcan - KB410F; for email, click here, office hours: anytime, lab sessions: Thu 13:00-14:00 as determined by a poll.

Contents: Measurement scales. Descriptive statistics. Review of probability and distributions. Review of program and data structures in a structured programming language. Frequentist vs. Bayesian. Measures of central tendency and dispersion. Poisson and binomial processes and hypothesis testing. Variance analysis. Least squares, maximum likelihood. Error analysis and propagation. Monte Carlo simulation and its applications.

Prerequisites: Math 252 and computer literacy (Phys 290 or Cmpe 150 or consent of instructor).

Recommended main text:Statistics, A Guide to the Use of Statistical Methods in the Physical Sciences, by Roger Barlow.

Additional Material:

  1. Proceedings of PHYSTAT 2003 - a workshop on statistical problems in particle physics, astrophysics and cosmology

  2. Probability, statistics and Monte Carlo review sections from the Particle Data Group, 2012 Review of Particle Physics (J. Beringer et al., Phys. Rev. D86, 010001, 2012).

Software: SPSS 20 (Bogazici license) or GNU PSPP 0.7.9 and ROOT (please make sure that PyROOT is installed if your programming background is mainly Python instead of C/C++).

Attendance: Students are encouraged to come to class regularly and be prepared to discuss the class material and are expected to have worked on the suggested problems/projects. Regular attendance benefits the learning environment in the class, allows statistically meaningful polls on topics to be taken, and provides a decent mood for lively discussion. It also helps keep everybody on the same page. It might also provide bonuses to your grades.