TLÜ ÕIS

Quantitative Data Analysis I

Course code

RAS6013.YK

old course code

Course title in Estonian

Kvantitatiivne andmeanalüüs I

Course title in English

Quantitative Data Analysis I

ECTS credits

5.0

Assessment form

Examination

lecturer of 2024/2025 Spring semester

- Farhat-Ul-Ain (language of instruction:English)

lecturer of 2025/2026 Autumn semester

Not opened for teaching. Click the study programme link below to see the nominal division schedule.

Course aims

After the course the student can conduct descriptive and inferential analysis of social scientific data including: select appropriate analysis methods, make statistical data transformations, present results and make inferences.

Brief description of the course

The course consists of lectures-seminars and practical sessions, where students are
expected to actively participate in thinking and working.
For lectures-seminars, students must work through the literature and tasks given by the
lecturer, knowledge and solution of which is checked during discussions in
lectures/seminars. In practical sessions, students learn to get to know and handle the
data and data processing using Jamovi, and what they have learned in the lecture is put
into practice in the form of practical examples and
exercises.
The following topics are covered in the course:
- Population and sample; data and characteristics;
- Distribution of a characteristic and parameters summarizing it. One- and two-
dimensional (cross-tabulation) descriptive analysis;
- Visualization and presentation of data and results (drawings);
- Simpler data transformations;
- Statistical inferences and testing: the main idea
- Relationships between characteristics, correlation coefficients
In addition to lectures-practical sessions, two group homework assignments and four
individual home assignments consisting of theoretical and practical data analysis tasks
within the scope of the material covered in the course must be submitted to pass the
course. The homework assignment requires independent work with data using the
Jamovi and presentation of the analysis results

Learning outcomes in the course

Upon completing the course the student:
- understands the theoretical foundations of descriptive and inferential statistics and their use in social science research;
- has practical skills to implement the acquired theoretical knowledge by carrying out data analysis, presentation and interpretation of results;
- presents analysis results and makes statistical inferences;
- chooses appropriate data analysis methods among the variety of methods covered in the course;
- uses Excel for data analysis on an intermediate level independently.

Teacher

Kadri Täht, Pauline Kommer

The course is a prerequisite

Data Analysis in Excel (RAS6016.YK)
Quantitative Data Analysis II (RAS6014.YK)

Study programmes containing that course