Universität Wien

220077 UE UE Applied Data Analysis (2018W)

3.00 ECTS (2.00 SWS), SPL 22 - Publizistik- und Kommunikationswissenschaft
Continuous assessment of course work

Registration/Deregistration

Note: The time of your registration within the registration period has no effect on the allocation of places (no first come, first served).

Details

max. 30 participants
Language: English

Lecturers

Classes (iCal) - next class is marked with N

"UE Applied Data Analysis" is complementary to "VO Introduction to Data Analysis". The course will start wit the VO on Oct 16. From then onwards, we will meet every week (UE/VO altering), except for the winter break. The last meeting, in which we will also write the exam, takes place on Jan 29.

  • Tuesday 23.10. 13:15 - 14:45 EDV-Raum 4 2C502 5.OG UZA II
  • Tuesday 06.11. 13:15 - 14:45 EDV-Raum 4 2C502 5.OG UZA II
  • Tuesday 20.11. 13:15 - 14:45 EDV-Raum 4 2C502 5.OG UZA II
  • Tuesday 04.12. 13:15 - 14:45 EDV-Raum 4 2C502 5.OG UZA II
  • Tuesday 08.01. 13:15 - 14:45 EDV-Raum 4 2C502 5.OG UZA II
  • Tuesday 22.01. 13:15 - 14:45 EDV-Raum 4 2C502 5.OG UZA II

Information

Aims, contents and method of the course

The objective of this class is to make students acquaintance with basic theoretical and practical statistical and quantitative research concepts in communication research. After the completion of the class, students should be able to plan and construct most commonly needed quantitative analyses in our field based on their own quantitative research designs.

The content of the class will generically cover fundamental mathematical processes for all statistical tests. However, more emphasis will be placed on the general understanding of all necessary methodological concepts to execute quantitative empirical tests with R.

Students will be proficient interpreting R outputs, creating tables ready to be published in academic journals, and discussing as well as interpreting most common quantitative findings in our field.
In sum, the overall goal of the class is to provide students with the necessary conceptual and practical skills to feel comfortable collecting and analyzing data based on their own research questions and designs.

In order to do so, the following topics will be covered:

Introduction to Statistical Methods (e.g., mean, variance, standard deviation)
Introduction to R / R workspace
R Data Handling (enter, edit and save data)
Exploring Assumptions for Analyses
Exploring Data with Graphs in R (scatterplot, histograms, boxplots)
Correlation
Regression
Exploratory Factor Analysis
Comparing Two Means (T-Test)
ANOVA / ANCOVA
Elective topics: Logistic Regression, MANOVA, Latex etc.

Attention: The courses VO Introduction to Data Analysis and UE Applied Data Analysis are linked. Phases of lecture and exercise will alternate.

Assessment and permitted materials

Assessment will be based on the following course requirements:
Participation and Attendance
Exercises: In-Class / Homework

Minimum requirements and assessment criteria

Examination topics

Reading list

Association in the course directory

Last modified: Sa 02.04.2022 00:23