psy110 - Research methods (Veranstaltungsübersicht)

psy110 - Research methods (Veranstaltungsübersicht)

Department für Psychologie 12 KP
Modulteile Semesterveranstaltungen Wintersemester 2021/2022 Prüfungsleistung
Vorlesung
  • Kein Zugang 6.02.111_1L - Multivariate statistics I Lehrende anzeigen
    • Prof. Dr. Andrea Hildebrandt

    Mittwoch: 08:15 - 09:45, wöchentlich (ab 20.10.2021)
    Termine am Montag, 14.02.2022 14:00 - 18:00, Montag, 21.02.2022 08:00 - 10:00, Freitag, 29.04.2022 16:15 - 18:15
    hybrid 59 students can attend in presence, the others can watch the recoreded lectures online. For participation in presence, you need to register for each session you want to attend by signing up to the respective group. The class in only open for Neurocognitive Psychology, Neuroscience and PhD students, NOT for Biology students.
Seminar
(
R seminar in summer is voluntary
)
  • Kein Zugang 6.02.001 - Introductory Course Statistics Lehrende anzeigen
    • Prof. Dr. Andrea Hildebrandt

    Freitag: 12:15 - 17:45, wöchentlich (ab 22.10.2021)
    Hybrid 59 students can attend in presence (3G), the others can attend online. For participation in presence, you need to register for each session you want to attend by signing up to the respective group. This course is designed for students who are completely new to the world of statistics and for those who have the feeling that many statistical concepts they learned about earlier are not present to them anymore. Relying on theoretical input and applied exercises, this interactive lecture covers all those topics that need to belong to students’ procedural knowledge in order to be able to follow the topics covered by the Psychological methods module. Course contents • Empirical research, variables and scales • Statistical parameter • Graphical data visualization • Probability theory • Probability distributions • Statistical sampling • Hypothesis testing • Testing hypothesis on differences • Correlation • Simple linear regression
  • Kein Zugang 6.02.111_2_Gr1 - analysis methods with R - group 1 in presence Lehrende anzeigen
    • Juan Felipe Quinones Sanchez

    Mittwoch: 12:15 - 13:45, wöchentlich (ab 20.10.2021)
    presence Classes will take place in the lecture hall. Students will work on online R tutorials and the teacher will answer questions.
  • Kein Zugang 6.02.111_2_Gr2 - analysis methods with R - group 2 online Lehrende anzeigen
    • Juan Felipe Quinones Sanchez

    Mittwoch: 16:15 - 17:45, wöchentlich (ab 20.10.2021)
    online The first 3 classes will take place as BBB sessions, the other classes online with R markdown tutorials and BBB Q&A sessions from 16-17h. The course is open for Neurocognitive Psychology and Neuroscience students.
Tutorium
(
statistics
)
  • Kein Zugang A learning tree for basic statistics Lehrende anzeigen
    • Prof. Dr. Andrea Hildebrandt

    Die Zeiten der Veranstaltung stehen nicht fest.
  • Kein Zugang 6.02.111_1T - Multivariate statistics I (Tutorial) Lehrende anzeigen
    • Prof. Dr. Andrea Hildebrandt
    • Maira Keller

    Dienstag: 16:15 - 17:45, wöchentlich (ab 19.10.2021)
    hybrid 59 students can attend in presence (3G), the others can attend online. For participation in presence, you need to register for each session you want to attend by signing up to the respective group. Additonal voluntary tutorial for the multivariate statistics lecture. If you are from another study program, please contact the teacher.
Hinweise zum Modul
Teilnahmevoraussetzungen
Enrolment in Master's programme Neurocognitive Psychology. Module psy110 is only relevant for students who started their studies before winter term 21/22. (All other students study modules psy111 and psy112.)
Prüfungsleistung Modul
The module will be tested with an oral exam (20 min).

Required active participation for gaining credits:
attendance of at least 70% in the seminars (use attendance sheet that will be handed out in the beginning of the term).
Kompetenzziele
Goals of module:
Students will acquire basic knowledge in planning empirical investigations, managing and
understanding quantitative data and conducting a wide variety of multivariate statistical
analyses. They will learn how to use the statistical methodology in terms of good scientific
practice and how to interpret, evaluate and synthesize empirical results from the perspective of
statistical modeling and statistical learning in basic and applied research context. The courses in
this module will additionally point out statistical misconceptions and help students to overcome
them.

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