Advanced Quantitative Data Analysis
Course code
KAD8069.HR
old course code
Course title in Estonian
Kvantitatiivne andmeanalüüs edasijõudnutele
Course title in English
Advanced Quantitative Data Analysis
ECTS credits
4.0
Assessment form
assessment
lecturer of 2023/2024 Spring semester
Anna-Liisa Jõgi (language of instruction:English)
lecturer of 2024/2025 Autumn semester
Not opened for teaching. Click the study programme link below to see the nominal division schedule.
Course aims
- To give an overview of advanced quantitative data analysis methods used in social and behavioural sciences;
- To practice analysing longitudinal and multilevel data and psychometrics;
- To support doctoral students in analysing quantitative data related to their doctoral thesis;
- To support critical thinking about different quantitative data analysis methods used in social and behavioural sciences.
- To practice analysing longitudinal and multilevel data and psychometrics;
- To support doctoral students in analysing quantitative data related to their doctoral thesis;
- To support critical thinking about different quantitative data analysis methods used in social and behavioural sciences.
Brief description of the course
The course gives an overview of the advanced quantitative data analysis methods used in the social and behavioural sciences. Course topics are:
1. Opportunities and assumptions of quantitative data and analysis
2. Moderation in regression analysis
3. Data analysis in experimental/intervention design
4. Data analysis in longitudinal design
5. Data analysis in multilevel design
6. Latent profile/class analysis
7. Confirmatory factor analysis and measurement invariance
The discussion of each topic is based on one scientific paper from the social and behavioural sciences field that has employed the particular type of data or analysis method.
Independent work:
To read one scientific paper for each seminar, prepare at least two critical questions about the data analysis of the paper, and write an approximately 200-words summary of the paper. Critical questions and a summary must be uploaded to the course e-environment no later than the day after the seminar.
1. Opportunities and assumptions of quantitative data and analysis
2. Moderation in regression analysis
3. Data analysis in experimental/intervention design
4. Data analysis in longitudinal design
5. Data analysis in multilevel design
6. Latent profile/class analysis
7. Confirmatory factor analysis and measurement invariance
The discussion of each topic is based on one scientific paper from the social and behavioural sciences field that has employed the particular type of data or analysis method.
Independent work:
To read one scientific paper for each seminar, prepare at least two critical questions about the data analysis of the paper, and write an approximately 200-words summary of the paper. Critical questions and a summary must be uploaded to the course e-environment no later than the day after the seminar.
Learning outcomes in the course
Upon completing the course the student:
- has got an overview of the quantitative data analysis methods used in social and behavioural sciences;
- has practiced analysing longitudinal and multilevel data and psychometrics;
- has got answers to the questions related to the quantitative data analysis in their work;
- is able to analyse critically quantitative data analysis methods used in social and behavioural sciences.
- has got an overview of the quantitative data analysis methods used in social and behavioural sciences;
- has practiced analysing longitudinal and multilevel data and psychometrics;
- has got answers to the questions related to the quantitative data analysis in their work;
- is able to analyse critically quantitative data analysis methods used in social and behavioural sciences.
Teacher
Anna-Liisa Jõgi
Additional information
To complete the course, it is required to:
- Participate actively in at least 70% of contact seminars;
- Submit summaries of all research papers covered in the course by the deadlines.
Participants are expected to be prepared for each seminar. Summaries of research papers must be within the given word limit, written in own words, and in good Estonian or English language.
- Participate actively in at least 70% of contact seminars;
- Submit summaries of all research papers covered in the course by the deadlines.
Participants are expected to be prepared for each seminar. Summaries of research papers must be within the given word limit, written in own words, and in good Estonian or English language.
Study programmes containing that course