WiSe 18/19: Linear and Logistics Regression Analysis
Excellent journal articles in sociology often use advanced statistical methods to analyze quantitative data. The in-depth knowledge of linear regression models, including their assumptions, is key ... read more
Excellent journal articles in sociology often use advanced statistical methods to analyze quantitative data. The in-depth knowledge of linear regression models, including their assumptions, is key for the understanding of more advanced methods. This course offers an introduction to linear regression analysis, its assumptions and diagnostics, and it provides numerous examples to exercise the correct interpretation of regression results. The course has its focus on continuous dependent variables, but it offers an introduction to categorical data analysis as well, including binary and multinomial logistic regression models.
The course starts at an intermediate level. We will use the statistical software package Stata in class.
Most of the sessions take place in a seminar room with a lecture-type introduction to linear regression analysis. Some sessions take place in a computer lab with exercises. After all sessions, students have the opportunity to use the computer lab to exercise.
The requirements for the course include four assignments. For each assignment, students compute some analyses in Stata and write-up an interpretation of the results.
Please register in advance via email to the instructor as the number of places is restricted. Please note there is a similar course offered as a block seminar this semester.