Data Analysis: Longitudinal Data, Linear and Logistic Regression
Course code
RAS6241.YK
old course code
RAS6241
Course title in Estonian
Andmeanalüüs: longituudsed andmed, lineaarne ja logistiline regressioon
Course title in English
Data Analysis: Longitudinal Data, Linear and Logistic Regression
ECTS credits
5.0
Assessment form
Examination
lecturer of 2023/2024 Spring semester
Not opened for teaching. Click the study programme link below to see the nominal division schedule.
lecturer of 2024/2025 Autumn semester
Not opened for teaching. Click the study programme link below to see the nominal division schedule.
Course aims
The objective of the course is to give an overview of different methods of multivariate statistical analysis and to create opportunities of developing skills for using these methods in research.
Brief description of the course
The course consists of three parts, every part is arranged as series of lectures and computer classes. In the lectures, there will be given an introduction to the method and it's application in previous sociological studies. Special attention is paid to testing hypotheses and presenting and interpreting the results.
Every part focuses on one selected method. In the first part, analysis of stability and of changes on the group and individual level using crosstabulation and comparison of means will be discussed; in the second part, linear regression analysis; in the third part, logistic regression analysis.
Every part will be completed with an assignment, where students have to apply the studied method: test hypotheses, present results, interpret.
The subject is meant both for bachelor as well as master students who have not participated in the course before. For BA and MA students, the load of homework will be different and higher requirements will be applied on the assignments of Master students.
Every part focuses on one selected method. In the first part, analysis of stability and of changes on the group and individual level using crosstabulation and comparison of means will be discussed; in the second part, linear regression analysis; in the third part, logistic regression analysis.
Every part will be completed with an assignment, where students have to apply the studied method: test hypotheses, present results, interpret.
The subject is meant both for bachelor as well as master students who have not participated in the course before. For BA and MA students, the load of homework will be different and higher requirements will be applied on the assignments of Master students.
Learning outcomes in the course
Upon completing the course the student:
- depending on the exercise, is able to choose appropriate method for the analysis;
- is able to carry out the respective analysis using SPSS;
- is able to interpret and present the findings.
- depending on the exercise, is able to choose appropriate method for the analysis;
- is able to carry out the respective analysis using SPSS;
- is able to interpret and present the findings.
Teacher
Professor Ellu Saar, CSc
Prerequisite course 1
Prerequisite course 2
Study programmes containing that course