Prof. Dr. Luca Amendola

Institut für Theoretische Physik -- Universität Heidelberg

Philosophenweg 16 -- D-69120 Heidelberg -- Germany

Tel: +49-6221-549-407 -- Fax: +49-6221-549-333

Sprechstunde: After my lectures
and by appointment Tuesday 11.00 - 12.00 a.m. (other times also possible)

  Computational Statistics
LSF info page LSF info

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.

   - 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: beginning of the winter semester (same rules as above)


    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)


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