Data Analysis II
Course code
old course code
Course title in Estonian
Andmeanalüüs II
Course title in English
Data Analysis II
ECTS credits
Assessment form
lecturer of 2022/2023 Autumn semester
Kairi Osula (language of instruction:Estonian)
Kaja Mädamürk (language of instruction:Estonian)
lecturer of 2022/2023 Spring semester
Not opened for teaching. Click the study programme link below to see the nominal division schedule.
Course aims
* To create opportunities for acquiring theoretical knowledge and practical skills for processing statistical data and carrying out elementary data analysis with the aid of SPSS software.
* The course is also set up to support developing ones ability to chose appropriate methods for analysis and presentation, as well as to understand and interpret correctly the meaning of statistical results.
Brief description of the course
* Comparing categories. Clustered and stacked barcharts.
* Parametric and nonparametric tests.
* Tests of statistical significance: t test
* ANOVA, Kruskal-Wallis test.
* Chi-square test, U test.

Course consists of seminar type lectures and practical classes where students are expected to be actively involved. In addition every student must submit home assignment, where (s)he demonstrates the command of all statistical data analysis techniques presented in the course.
Learning outcomes in the course
Upon completing the course the student:
- understands of main concepts of descriptive and inferential statistics, knowledge of prerequisites for their correct application and ability to interpret the results of the analysis correctly;
- has ability to recognise different types of variables and choose appropriate statistical techniques accordingly;
- has knowledge of main and the most important terminology of data analysis;
- has skills to structure the research while writing up and format the thesis according to the requirements;
- has skills to use the SPSS software with the aid of the manual for simple data processing and analysis.
- explains the difference between descriptive and inferential statistics.
Kairi Osula