Prof. Dr. Luca Amendola
Tel: +49-6221-549-407 -- Fax: +49-6221-549-333 Sprechstunde:
After my lectures |
Summer Semester 2022
Info on coronavirus measures at the University is below. Please read it carefully.Information on Covid measures
Info on data collection and protection
The course is an introduction to statistical analysis, with emphasis on computational methods. We will use Python for some exercises, but students can use their preferred programming language (e.g. Mathematica, R, etc), or even pseudo-code.
Program
- Random variables
- Probability distribution functions
- Moments, generating function, central limit theorem etc
- Bayes theorem
- Linear and non-linear regression
- Estimators (maximum likelihood, robust estimators etc)
- Hypothesis testing (non-parametric, multiple, etc)
- Cluster analysis
- Principal Component Analysis
- Bayesian model selection
- Fisher matrix
- Random fields
NOTE: Course begins on April 20th, 2022
Classes on Wednesday 9:15-11:00 in INF 227 SR 1.403/4
Exercise classes start on the week of April, 25th
Exam on August 11th, 9:00-12:00, INF 308 HS1. You can bring a hand-written page A4 cheat sheet with all the formulae you can write. You can also bring a calculator without internet or phone connection. Remember to bring a valid ID for identification.
Second exam: Oct. 21, 2-6pm, INF 308 HS2 (same rules as above)
Calendar:
20.04
27.04
04.05
11.05
18.05
25.05
01.06
08.06
15.06
22.06
06.07
13.07
20.07
CREDITS: 6
During the course homework sheets will be handed out (you will be able to download them from this page). They will count towards admission to the final written exam.
You can work in pairs. Please put your names and tutorial group on every page!
Exercise sheet 1
Exercise sheet 2
Exercise sheet 3
Exercise sheet 4
Exercise sheet 5
Exercise sheet 6
Exercise sheet 7
Exercise sheet 8
Exercise sheet 9
Exercise sheet 10
Exercise sheet 11 (Not graded)
Suggested texts:
Lecture notes
DeGroot and Schervish, Probability and Statistics, Addison Wesley
P. Gregory, Bayesian Logical Data Analysis for the Physical Sciences, Cambridge University Press
Introduction to R
(an introductory manual on R language)
