No more than 12 students of other study tracks or programmes will be admitted. Priority is given for the sociology and demography students who are using quantitative methods in their Master's Thesis. Depending on the available student places, students of other Master’s programmes can be accepted on a case-to-case basis.
Compulsory prior studies:
• The course Quantitative Research Skills for Social Sciences (10 cr) must be completed no later than at the same time as this course.
• Students must already have begun their participation in the Master’s seminar in demography.
Recommended prior studies:
Students will learn to conduct quantitative analysis with the Stata software and interpret the results. Students will learn to look for and summarise research literature related to their research question, central research results and data requirements, as well as evaluate the quality of prior research. After completing the course, students will be able to evaluate the reliability and limitations of quantitative research results (those of their own and others).
4. periodi (Väestötieteen pro maisteriseminaarin oltua käynnissä yhden periodin)
A practical course where the participants of the Master’s seminar in demography are able to apply statistical modelling, in a controlled environment, with the material collected for their Master’s thesis and discuss specific statistical questions related to their research. Students will also be steered to look for scientific studies related to the topic of their Master's thesis by using several databases, in addition to which methods for managing literature sources will be introduced. Additionally, students will attain abilities for evaluating and comparing the results and quality of research for the literature review included in their Master’s thesis. The Stata statistics software will be used during the course, which will focus on practical assignments.
Related literature will be announced during the course.
Graded on a scale of 0 to 5 (0 = Fail, 1 = Passable, 2 = Satisfactory, 3 = Good, 4 = Very Good, 5 = Excellent)
Contact teaching in the IT classroom, assignments and peer reviews