Regression analysis in educational research, 7.5 credits
Regression analysis is the most commonly used method to answer questions regarding relationships between variables and groups. This technique is valuable and fundamental to empirically address many educational research questions. Examples are: How do parents and siblings affect the school outcomes of a child? How does school climate and students' socioeconomic composition impact average school achievement? What are the factors that may affect the probability for a student to choose a school that is located outside his/her residential area?
If you have similar research questions and wonder what methods are suitable to analyse them, then this is the course for you!
This course will encourage participants to predict an outcome of interest and to examine causal links between the outcome variable and a set of possible explanatory variables using analytical tools. Depending on the measurement level of the outcome variable, the course focuses on two different types of regression models, namely, linear regression analysis in which the dependent variable is continuous, and logistic regression analysis where the dependent variable is binary. This is an applied course. Participants will gain both theoretical knowledge and practical experience.
The course provides a foundation for the more advanced courses in the QRM research school, but it can also be read independently. It is well suited for doctoral students, researchers and supervisors who want to refresh and further develop knowledge that they acquired long ago.
The course is open to Swedish and international participants.
Entry requirements
Knowledge equivalent to the learning goals in QRMs course Basic statistics for educational research (QRM1800).
Course code
QRM1802
Application period
Fall 2024: 2024-04-01 - 2024-06-02