Modern Statistical Data Analysis for Practitioners

1st Lecture:

Thursday November 1st 2018, 09:30 s.t.

Seminarraum __.401
Fachbereich 13 Physik,
Institut für Biophysik,
Max-von-Laue-Str. 1, Goethe-Uni Frankfurt
Lecturers: Dr. Jürgen Köfinger, Dr. Roberto Covino, Dr. Lukas Stelzl

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Content of the course
We introduce the basics of probability theory, classical statistics, and
classical error analysis (p-values, confidence intervals), which serves
as the starting point to explore modern methods of statistics (Maximum
Likelihood, Bayes). We use these methods to extract information from
noisy data through (non-) linear parameter estimation (fitting) and
model comparison. We show how to analyze data containing dynamical
information by time series analysis (correlation functions, error
analysis) and Markov-Chain models and kinetic models described by rate

 1. Crash course in statistics
     1. Elements of probability theory
     2. Central limit theorem and error of the mean
     3. Classical error analysis and error propagation
     4. Confidence intervals and p-values
     5. Statistical tests
     6. Maximum likelihood estimation
     7. Bayesian inference
 2. Model fitting
     1. Linear models
     2. Non-linear models
     3. Model comparison
 3. Time series analysis
     1. Autocorrelations
     2. Block-averaging
     3. Bootstrapping / Jackknifing
 4. Markov-chains and kinetic models
     1. Master equation
     2. Monte Carlo sampling
     3. Uncertainty quantification using Monte Carlo sampling

Goal of the course
To overarching goal is to equip the students with the necessary
statistical tools to extract information from noisy data reliably and
with quantified uncertainties. The students should be able to identify
the common pitfalls of statistical data analysis in their own work and
be able to critically assess the quality of published data and
statistical analysis. These goals will be practised in the practical
course on real world examples.


Max-Planck-Institut für Biophysik

Statistical data analysis for practitioners
Dr. Jürgen Köfinger
Dr. Roberto Covino
Dr. Lukas Stelzl
Abteilung Theoretische Biophysik

Tel.: +49 (0) 69 6303-2503
E-Mail: juergen.koefinger(at)

Course documentation

Course announcement