PAP334 Statistical Methods
A 5 ECTS credit course autumn 2024
General Information
Lectures Fridays 10.15-12.00
Physicum E205
Weeks 37-41, 44-48, 50
Exercise session Fridays 14.15-15.00
Physicum E205
Starting week 39
Lectures: Professor Kenneth Österberg
E-mail: kenneth.osterberg(at)helsinki.fi
Exercises: PhD Fredrik Oljemark
E-mail: fredrik.oljemark(at)helsinki.fi
Course and Supporting Material
- Lecture notes available here (pdf)
- Selected lecture recordings from previous years available here (mp4)
- Literature:
G. Cowan: Statistical Data Analysis (Oxford University Press 1998)
- A comprehensive reference of Statistical Methods in Physics. Contains both theoretical background and practical examples. Highly recommended.
Particle Data Group Reviews on Probability, Statistics, Monte Carlo techniques & Machine Learning (freely available on the web)
- Good but rather condensed summaries. Written by the same author, G. Cowan, except Machine Learning summary.
C. Walck: Hand-book on statistical distributions for experimentalists (freely available on the web)
- An opus on statistical distributions. When knowing your physics distribution, useful for finding out distribution characteristics and how to generate them.
- Coding examples and help:
Matlab examples
Data analysis with Python
Simulation examples with Python
SimPy simulation examples with Python- Description of SimPy
Course Content
The course should provide the student a firm basis to statistically correctly analyze data from a physics experiment and do a valid interpretation of the result.
- Fundamental concepts: experimental uncertainties and their correct interpretation, frequentist & Bayesian interpretation of probability, the most common distributions and their applications.
- Monte Carlo methods & statistical tests: basics of Monte Carlo methods, the concept of hypothesis and test statistic, rejection of a hypothesis & different methods for hypothesis testing
- Parameter & uncertainty estimation: the concept of estimation, the maximum likelihood method (suurimman uskottavuuden menetelmä) and the method of least squares (pienimmän neliösumman menetelmä).
- Confidence intervals & Unfolding
Course Grading (for autumn 2024)
Exercises (9-10 papers) gives at maximum 36 points (weight: 50 %),
Home exam gives at maximum 36 points (weight: 50 %),
Written exam gives at maximum 36 points (weight: 50 %).
The two best of these three will be used for making the course grade
(you may choose to do only one out of the two exams if you wish).
Exercises
Exercises given latest on Thursdays, notification by e-mail, to be returned following Thursday before 12.00 Finnish time.
Exercise paper available and your solutions to be returned on the moodle course page
Model answers to exercises available on moodle course page
Course exam
Home exam: Wed 8.1.2025 10.00 - Fri 10.1.2025 17.00
AND/OR
General exam: Fri 14.2.2025 12.00-16.00 in Chemical A110 (registration by Tue 4.2.2025 through SISU)
Results (home exam + exercises) and grade of course
Previous departmental/general exams: 24.8.2017 19.1.2018 18.1.2019 17.1.2020 22.1.2021 16.2.2024.
Other News
First lecture on Fri 13.9.2024 at 10.15!
Extra lecture about ROOT & TMVA on Friday 18.10.2024 at 10.15!
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Send any comments or questions about this page to kenneth.osterberg(at)helsinki.fi