Applied data analysis for psychology using the open-source software R [Data Analysis using R]

Dozent/in:

Alexander Pastukhov

Angaben:

Seminar, 2 SWS, ECTS: 3

Termine:

Di, 14:00 - 16:00, Raum n.V.

Voraussetzungen / Organisatorisches:

No programming background necessary, basic knowledge on statistical analysis is advantages but not strictly necessary. For Ba / Ma Psychology only!

Inhalt:

Modern psychologies relies on data science. R is the premiere free software that is widely used both in seminars and in the industry.

Learning Goals: This introductory course into R, will teach you everything you need to know; how to import the data, preprocess it, summarize it, plot it, analyze it and create a visually appealing final report. At the end, you will able to preprocess, analyze, and plot data for you Bachelor/Master/PhD thesis.

Course Method: This seminar assumes no prior knowledge on your part. We will start with basic concepts of variables and functions and proceeding to advanced topics. The course will introduce different ways to perform typical data analysis tasks. You can bring your own data but you do not have to.

Grading: In the course, you will complete numerous practical exercises. Completing 80% of them is required to pass the course.

Empfohlene Literatur:

Course syllables are available online: https://alexander-pastukhov.github.io/data-analysis-using-r-for-psychology/
"R for Data Science" by Garrett Grolemund and Hadley Wickham available freely at http://r4ds.had.co.nz/

Schlagwörter:

statistical analysis, data science, statistics

Cognitive reading club

Dozentinnen/Dozenten:

Alexander Pastukhov, Claus-Christian Carbon

Angaben:

Seminar, nur nach vorheriger Anmeldung bei Prof. Carbon

Termine:

Di, 14:00 - 16:00, Raum n.V.

Voraussetzungen / Organisatorisches:

Für Studierende, die eine Forschungs- oder Seminararbeit im Bereich der kognitiven Psychologie schreiben.

Linear Algebra: Theory, Intuition, Code [Linear Algebra]

Dozent/in:

Alexander Pastukhov

Angaben:

Seminar, 2 SWS, ECTS: 3

Termine:

Do, 12:00 - 14:00, M3N/03.29

Voraussetzungen / Organisatorisches:

The course does not require any mathematical background beyond school algebra. Basic knowledge of R or Python is advantageous but not required.

Inhalt:

This is a book-club style seminar for those who are interested developing intuition about linear algebra. Linear algebra is at the heart of science acting as a foundation statistics and applied modelling. The book and the course focus on key concepts that are critical to developing an intuition of how applied tools, such as statistical models fitting procedures, work. The course does not require any mathematical background beyond school algebra. Basic knowledge of R or Python is advantageous but not required.

Empfohlene Literatur:

"Linear Algebra: Theory, Intuition, Code" by Mike X Cohen

Python for social and experimental psychology

Dozent/in:

Alexander Pastukhov

Angaben:

Seminar, ECTS: 3

Termine:

Mo, 8:00 - 10:00, M3N/-1.19

Voraussetzungen / Organisatorisches:

No prior programming skills required. For Ba / Ma Psychology only!

Inhalt:

An introductory hands-on course that teaches how to use Python to create experimental programs. No prior knowledge is required, as we will start with introduction to programming in Python by writing games (because psychological experiments are merely boring games). We will progress from basic text based interaction to using graphics and sound using PsychoPy library.

Learning Goal: This course is especially tailored to your needs as a student in the humanities. The aim of the course is to develop good programming habits and skills to write a clear and concise code. You will learn all necessary material starting from basic variables and functions, proceeding to conditional statements, list, and dictionaries, and further to more advanced topics of using classes and object-oriented programming. By the end of the seminar, you will be able to program a custom experiment with all necessary components including settings files, custom stimuli, data logging, dynamic feedback, etc.

Course Method: Together we will program games (because as I told you, psychological experiments are merely boring games), including familiar favorites such as "Snake", "Memory", "Space invaders", or "Guitar Hero" using field-standard PsychoPy library.

Grading: In the course, you will complete numerous practical exercises. Completing 80% of them is required to pass the course.

Empfohlene Literatur:

The course material is available online at https://alexander-pastukhov.github.io/writing-games-with-python-and-psychopy/

Statistical Rethinking [Statistical Rethinking]

Dozent/in:

Alexander Pastukhov

Angaben:

Sonstige Lehrveranstaltung, 2 SWS, ECTS: 3

Termine:

Mi, 14:00 - 16:00, Raum n.V.

Voraussetzungen / Organisatorisches:

Some Bachelor level knowledge of statistics and R is beneficial, but no prior knowledge beyond high school algebra is required! For Ba / Ma Psychology only!

Inhalt:

Do you find statistics confusing and complicated? Do you want to improve and better understand your analysis? Do you want to find out that you are already a Bayesian statistician? Then this seminar is for you.

Learning Goals: In this seminar, you will learn how to build a statistical model from the ground up with the goal of being able to build a customized model for any statistical problem and analysis. After this course you will understand that a linear regression, a T-test, an ANOVA, or an ANOCOVA all refer to the same simple linear model that you can build yourself. The aim is to make sure that you will know exactly what your analysis does and why you are doing it in this way.

Course Method: This seminar assumes no prior knowledge on your part. We will start with a basic concept of probability-as-counting and proceed to understanding what statistical models are and how to build them. Over the course of the seminar, we will gradually move forward to more advanced topics learning how to handle various types of data, identify spurious associations, infer causality, evaluate models, or perform power analysis. Forming a book club we will read Statistical Rethinking by Richard McElrath. It is an excellent introductory statistics book that explain even most intimidating topics very clearly, links all seemingly discrepant topics together, and has plenty of examples in R. We will read one chapter every week and discuss the topics and questions during the seminar.

Empfohlene Literatur:

"Statistical Rethinking: A Bayesian Course with Examples in R and Stan" by Richard McElreath https://www.oreilly.com/library/view/statistical-rethinking/9781482253481/

Schlagwörter:

statistics, bayesian statistics