Stud.IP Uni Oldenburg
Universität Oldenburg
07.12.2021 01:09:42
psy112 - Research methods II - Statistical Learning (Vollständige Modulbeschreibung)
Originalfassung Englisch PDF Download
Modulbezeichnung Research methods II - Statistical Learning
Modulkürzel psy112
Kreditpunkte 6.0 KP
Workload 180 h
Einrichtungsverzeichnis Department für Psychologie
Verwendbarkeit des Moduls
  • Master Neurocognitive Psychology (Master) > Mastermodule
Zuständige Personen
Hildebrandt, Andrea (Modulverantwortung)
Hildebrandt, Andrea (Prüfungsberechtigt)
Teilnahmevoraussetzungen
Enrolment in Master's programme Neurocognitive Psychology.
Kompetenzziele
Goals of module:
Building upon the basic knowledge in multivariate statistical modeling covered in psy111, after completion of this module students will know how to deal with big data to address empirical questions in neurocognitive psychology. They will be able to solve prediction and classification problems to the realm of basic and applied statistical/machine learning purposes. Furthermore, students will understand the specifics of applied research and the statistical modeling of noisy, longitudinal data.

Competencies:
++ interdisciplinary kowledge & thinking
++ statistics & scientific programming
++ data presentation & discussion
+ independent research
+ scientific literature
++ ethics / good scientific practice / professional behavior
++ critical & analytical thinking
++ scientific communication skills
+ group work
Modulinhalte

Part 1: Statistical / machine learning methods

  • Supervised and unsupervised statistical learning and prediction
  • Resampling methods
  • Regularized regression
  • Linear and quadatic discriminant analysis
  • Naive Bayes algorithm
  • Tree-based methods
  • Support vector machines
  • The basics of neural networks
  • Principal component regression
  • Clustering methods
     

Part 2: Statistical / machine learning methods with R (voluntary seminar)

  • Data examples and applications of the basic machine learning methods covered in the lecture
     

Part 3: Evaluation research (seminar)

  • Paradigms and methods in applied evaluation research (quantitative, mixed-methods)
  • Types of studies and designs in evaluation research (experimental, quasi-experimental, (multiple) time series, etc.)
  • Multivariate statistical modeling of change over time and group differences in change
  • Specific statistical tools for sampling and matching (e.g., Propensity score matching)
  • Basics of causality theory and the estimation of average and conditional effects in EffectLiteR
  • Research synthesis and meta-analysis
Literaturempfehlungen
Links
Unterrichtssprache Englisch
Dauer in Semestern 1 Semester
Angebotsrhythmus Modul The module will start every summer term.
Aufnahmekapazität Modul unbegrenzt
Modullevel / module level MM (Mastermodul / Master module)
Modulart / typ of module Pflicht / Mandatory
Lehr-/Lernform / Teaching/Learning method Part 1: lecture; Parts 2 and 3: seminars; additional tutorials are offered.
Vorkenntnisse / Previous knowledge psy 111 Research methods I – Statistical Modeling
Lehrveranstaltungsform Kommentar SWS Angebotsrhythmus Workload Präsenz
Vorlesung
2 SoSe 28
Seminar
R seminar voluntary
2 SoSe 28
Tutorium
statistics
SoSe 0
Präsenzzeit Modul insgesamt 56 h
Prüfung Prüfungszeiten Prüfungsform
Gesamtmodul
end of summer term
The module will be tested with an oral exam (25 min).

Required active participation for gaining credits:
attendance of at least 70% in the mandatory seminar (use attendance sheet that will be handed out in the beginning of the term).