Module Number

INFO-4151 		Module Title

Applied Statistics II 		Lecture Type(s)

Lecture
ECTS 6
Work load
- Contact time
- Self study
Workload:
180 h
Class time:
60 h / 4 SWS
Self study:
120 h
Duration 1 Semester
Frequency In the summer semester
Language of instruction German
Type of Exam

Written Test
Content

Building on "Applied Statistics I" (german: "Angewandte Statistik I"), more complex statistical methods are covered: Generalized Linear Models (GLM), Principal Component Analysis (PCA), Independence Analysis (ICA), and Bayesian statistics. The emphasis is on the practical application of all methods and their implementation in Python (with the modules statsmodels, scipy.stats, sklearn and pymc) and the presentation of results in notebooks.
Objectives

The students know advanced statistical methods, how to use them and how to implement them in software. They can figure out the differences between frequentist and Bayesian statistics.
The students are able to plan and evaluate experiments themselves and to avoid typical errors in experimental design. They can critically evaluate the way statistical methods are and results are presented in the literature.
Allocation of credits / grading
Type of Class
Status
SWS
Credits
Type of Exam
Exam duration
Evaluation
Calculation
of Module (%)
Lecture
V
o
4
6.0
wt
90
g
100
Prerequisite for participation INF3223 Applied Statistics I,

INFM1010 Mathematics for Computer Science 1: Analysis,

INFM1020 Mathematics for Computer Science 2: Linear Algebra
Lecturer / Other Wannek
Literature

Wird in der Vorlesung bekannt gegeben
Last offered Sommersemester 2022
Planned for Sommersemester 2024
Assigned Study Areas INFO-INFO, INFO-PRAK, MEDI-APPL, MEDI-INFO, ML-CS