Data Analysis: Descriptive Statistics
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Course code
IFI7041.DT
old course code
IFI7041
Course title in Estonian
Andmeanalüüs: statistiline andmestik ja kirjeldav statistika
Course title in English
Data Analysis: Descriptive Statistics
ECTS credits
4.0
Assessment form
Examination
lecturer of 2022/2023 Autumn semester
Triinu Jesmin (language of instruction:English)
Kadri Mettis (language of instruction:Estonian)
Ülle Raavel (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 caring 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
Classification and main features of research approaches and methods. Basics of the data collection. Statistical data and preparation for analysis. Different types of data. Descriptive statistics: frequency and summary tables, statistics and charts. Relationships: measures of association and cross-tables. Course consists of seminars where students are expected to be actively involved.
Learning outcomes in the course
Upon completing the course the student:
- recognises and can comparatively differentiate between different types of research designs;
- knows what are the main quality criteria for academic research;
- can design simple instruments for data collection;
- can create statistical data-table with an appropriate structure;
- has got experience in setting up questions about data which lead to statistical analysis;
- understands main concepts of descriptive statistics, knows the prerequisites for their correct application and can interpret the results of the analysis correctly;
- can recognise different types of variables and choose appropriate statistical techniques accordingly;
- can use the statistical software with the aid of the manual for simple data processing and analysis.
Teacher
Kairi Osula, Triinu Jesmin, Jaanika Meigas
Additional information
Soovitav on omada eelteadmisi kontoritarkvara kasutamisest ja tabelarvutusest.
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Human-Computer Interaction (IFIMM/21.DT)
Digital Learning Games (DTLGM/21.DT)
Traffic Safety (HKLOR/20.HK)
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Applied Computer Science (HKIFR/19.HK)
Traffic Safety (HKLOR/19.HK)
Educational Technology (IFHTM/20.DT)
Digital Learning Games (DTLGM/20.DT)
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